MOTOR PARAMETERS INFLUENCE ON STABILITY OF DRIVE FOR INDUSTRIAL ROBOT

Sorin Enache, Monica Adela Enache, Mircea Dobriceanu, Mircea Adrian Drighiciu and Anca Petrisor

This paper analyzes a driving system for an industrial robot from the stability point of view. For doing this, an original analysis method has been conceived. The method has as starting point the two axes mathematical model with equations written in per unit values. A Matlab program has been conceived with their help; this program has led to results and conclusions detailed in this paper. Finally a series of experimental results confirming the conclusions deduced with the new method are presented.

EVOLUTION OF A MOBILE ROBOT’S NEUROCONTROLLER ON THE GRASPING TASK - Is Genetic also Generic?

Philippe Lucidarme

This paper presents a survey on the generic evolution of mobile robot’s neurocontrollers with a particular focus on the capacity to adapt these controllers in several environments. Several experiments on the example of the grasping task (autonomous vacuum cleaner for example) are performed and the results show that the produced neurocontroller is dedicated to the trained conditions and cannot be considered as generic. The last part of the paper discusses of the necessary changes in the fitness function in order to produce generic neurocontrollers.

OPTIMAL CONTROL WITH ADAPTIVE INTERNAL DYNAMICS MODELS

Djordje Mitrovic, Stefan Klanke and Sethu Vijayakumar

Optimal feedback control has been proposed as an attractive movement generation strategy in goal reaching tasks for anthropomorphic manipulator systems. The optimal feedback control law for systems with non-linear dynamics and non-quadratic costs can be found by iterative methods, such as the iterative Linear Quadratic Gaussian (iLQG) algorithm. So far this framework relied on an analytic form of the system dynamics, which may often be unknown, difficult to estimate for more realistic control systems or may be subject to frequent systematic changes. In this paper, we present a novel combination of learning a forward dynamics model within the iLQG framework. Utilising such adaptive internal models can compensate for complex dynamic perturbations of the controlled system in an online fashion. The specific adaptive framework introduced lends itself to a computationally more efficient implementation of the iLQG optimisation without sacrificing control accuracy - allowing the method to scale to large DoF systems.

LHTNDT: LEARN HTN METHOD PRECONDITIONS USING DECISION TREE

Fatemeh Nargesian and Gholamreza Ghassem-Sani

In this paper, we describe LHTNDT, an algorithm that learns the preconditions of HTN methods by examining plan traces produced by another planner. LHTNDT extracts conditions for applying methods by using decision tree algorithm. It considers the state of relevant domain objects in both current and goal state. Structurally repetitive training samples are removed using graph isomorphism. In our experiments, LHTNDT converged. It can learn most of preconditions correctly and almost quickly. Approximately 80% of test problems can be solved by preconditions extracted by ¾ of plan traces needed for full convergence.

FEEDING A GENETIC ALGORITHM WITH AN ANT COLONY FOR CONSTRAINED OPTIMIZATION - An Application to the Unit Commitment Problem

Guillaume Sandou, Stéphane Font, Sihem Tebbani, Arnaud Hiret and Christian Mondon

In this paper, a new optimisation strategy for the solution of the classical Unit Commitment problem is proposed. This problem is known to be an often large scale, mixed integer programming problem. Due to high combinatorial complexity, the exact solution is often intractable. Thus, a metaheuristic based method has to be used to compute a very often suitable solution. The main idea of the approach is to use ant colony algorithm, to explicitly deal with the feasibility of the solution, and to feed a genetic algorithm whose goal is to intensively explore the search space. Finally, results show that the proposed method leads to the tractable computation of satisfying solutions for the Unit Commitment problem.

SELF-ORGANISATION OF GAIT PATTERN TRANSITION - An Efficient Approach to Implementing Animal Gaits and Gait Transitions

Zhijun Yang, Juan Huo and Alan Murray

As an engine of almost all life phenomena, the motor information generated by the central nervous system (CNS) plays a critical role in the activities of all animals. Despite the difficulty of being physically identified, the central pattern generator (CPG), which is a concrete branch of studies on the CNS, is widely recognised to be responsible for generating rhythmic patterns. This paper presents a novel, macroscopic and model-independent approach to the retrieval of different patterns of coupled neural oscillations observed in biological CPGs during the control of legged locomotion. Based on the simple graph dynamics, various types of oscillatory building blocks (OBB) can be reconfigured for the production of complicated rhythmic patterns. Our quadrupedal locomotion experiments show that an OBB-based artificial CPG model alone can integrate all gait patterns and undergo self-organised gait transition between different patterns.

REDUCED ORDER H∞ SYNTHESIS USING A PARTICLE SWARM OPTIMIZATION METHOD

Guillaume Sandou, Gilles Duc and Patrick Boucher

Hinfinity controller synthesis is a well known design method for which efficient dedicated methods have been developed. However, such methods compute a full order controller which has often to be reduced to be implemented. Indeed, the reduced order Hinfinity synthesis is a non convex optimization problem due to rank constraints. In this paper, a particle swarm optimization method is used to solve such a problem. Numerical results show that the computed controller has a lower Hinfinity norm than the controller computed from a classical Hankel reduction of the full order Hinfinity controller.

OBTAINING MINIMUM VARIABILITY OWA OPERATORS UNDER A FUZZY LEVEL OF ORNESS

Kaj-Mikael Björk

Finding the optimal OWA (ordered weighted averaging) operators is important in many decision support problems. The OWA-operators enables the decision maker to model very different kinds of aggregator operators. The weights need to be, however, determined under some criteria, and can be found through the solution of some optimization problems. The important parameter called the level of orness may, in many cases, be uncertain to some degree. Decision makers are often able to estimate the level using fuzzy numbers. Therefore, this paper contributes to the current state of the art in OWA operators with a model that can determine the optimal (minimum variability) OWA operators under a (unsymmetrical triangular) fuzzy level of orness.

SYNCHRONIZATION OF ARM AND HAND ASSISTIVE ROBOTIC DEVICES TO IMPART ACTIVITIES OF DAILY LIVING TASKS

Duygun Erol and Nilanjan Sarkar

Recent research in rehabilitation indicates that tasks that focus on activities of daily living (ADL) is likely to show significant increase in motor recovery after stroke. Most ADL tasks require patients to coordinate their arm and hand movements to complete ADL tasks. This paper presents a new control approach for robot assisted rehabilitation of stroke patients that enables them to perform ADL tasks by providing controlled and coordinated assistance to both arm and hand movements. The control architecture uses hybrid system modelling technique which consists of a high-level controller for decision-making and two low-level assistive controllers (arm and hand controllers) for arm and hand motion assistance. The presented controller is implemented on a test-bed and the results of this implementation are presented to demonstrate the feasibility of the proposed control architecture.

DATA MINING AND KNOWLEDGE DISCOVERY FOR MONITORING AND INTELLIGENT CONTROL OF A WASTEWATER TREATMENT PLANT

S. Manesis, V. Deligiannis and M. Koutri

Intelligent control of medium-scale industrial processes has been applied with success but, as a method of advanced control, can be further improved. Since intelligent control makes use of knowledge-based techniques (such as expert systems, fuzzy logic, neural networks, etc.), a data mining and knowledge discovery subsystem embedded in a control system can support an intelligent controller to achieve a more reliable and robust operation of the controlled process. This paper proposes a combined intelligent control and data mining scheme for monitoring and mainly for controlling a wastewater treatment plant. The intelligent control system is implemented in a programmable logic controller, while the data mining and knowledge discovery system in a personal computer. The entire control system is basically a knowledge-based system which improves drastically the behavior of the wastewater treatment plant.

CONTROLLING INVESTMENT PROPORTION IN CYCLIC CHANGING ENVIRONMENTS

J.-Emeterio Navarro-Barrientos

In this paper, we present an investment strategy to control investment proportions for environments with cyclic changing returns on investment. In our approach, we consider an investment model where the agent decides at every time step the proportion of wealth to invest in a risky asset, keeping the rest of the budget in a risk-free asset. Every investment is evaluated in the market modeled by stylized returns on investment (RoI). For comparison reasons, we present two reference strategies which represent the case of agents with zero-knowledge and complete-knowledge of the dynamics of the RoI, and we consider also an investment strategy based on technical analysis. To account for the performance of the different strategies, we perform some computer experiments to calculate the average budget that can be obtained over a certain number of time steps. To assure for fair comparisons, we first tune the parameters of each strategy. Afterwards, we compare their performance for RoIs with fixed periodicity (stationary scenario) and for RoIs with changing periodicities (non-stationary scenario).

ENERGY MODEL BASED CONTROL FOR FORMING PROCESSES

Patrick Girard and Vincent Thomson

Thermoforming consists of shaping a plastic material by deforming it at an adequate deformation rate and temperature. It often exhibits abrupt switches between stable and unstable material behaviour that have neither been identified nor controlled up to now. PID control, although adequate for simple parts, has not been able to control very well the forming of complex parts and parts made of newer materials. In this paper, the state parameters that allow the development of predictive models for the forming process and the construction of control systems are identified. A robust, model based control system capable of in-cycle control is presented. It is based on a simulator continuously tuned and supported in real time by intelligent agents that incorporate diagnostic capabilities.

AUTOMATED SIZING OF ANALOG CIRCUITS BASED ON GENETIC ALGORITHM WITH PARAMETER ORTHOGONALIZATION PROCEDURE

Masanori Natsui and Yoshiaki Tadokorot

This paper presents a method for the automated sizing of analog circuits using genetic algorithm (GA). GA is a kind of optimization techniques based on natural selection and genetics. For the rapid and efficient exploration of GA, we introduce the idea of search space sphering and dimension reduction with principal component analysis (PCA). The potential capability of the system is demonstrated through the automated sizing of wide-swing current mirror circuit. Experimental results show that the search space optimization using PCA improves the search efficiency of the system, and the system can estimate sub-optimal parameter set successfully.

DESIGN OF NEURONAL NETWORK TO CONTROL SPIRULINA AQUACULTURE

Ernesto Ponce, Claudio Ponce and Bernardo Barraza

A neural network that was designed to control a Spirulina aquaculture process in a pilot plant in the north of Chile, is presented in this work. Spirulina is a super food, but is a delicate alga and its culture may be suddenly lost by rapid changes in the weather that can affect its temperature, salinity or pH. The neural network control system presented is complex and non linear, and has several variables. The previous automatic control system for the plant proved unable to cope with large climatic variations. The advantage of this new method is the improvement in efficiency of the process, and a reliable control system that is able to adapt to climatic changes. The future application of this work is related to the industrial production of food and fuel from micro algae culture, for the growing world population.

NONLINEAR SYSTEM IDENTIFICATION USING DISCRETE-TIME NEURAL NETWORKS WITH STABLE LEARNING ALGORITHM

Talel Korkobi, Mohamed Djemel and Mohamed Chtourou

This paper presents a stable neural sytem identification for nonlinear systems. An input output discrete time representation is considered. No a priori knowledge about the nonlinearities of the system is assumed. The proposed learning rule is a the backpropagation algorithm under the condition tha the learning rate belongs to a specified range defining the stability domain. Satisfying such condition, unstable phenomenon during the learning process is avoided. A Lyapunov analysis is made in order to extract the new updating formulations which contain a set of inequality constraints. In the constrained learning rate algorithm, the learning rate is updated at each iterative instant by an equation derived using the stability conditions. As a case study, identification of two discrete time systems are considered to demonstrate the effectiveness of the proposed algorithm. Simulation results concerning the considered systems are presented.

IMPROVEMENTS IN THE FIELD OF DEVICE INTEGRATION INTO AUTOMATION SYSTEMS WITH EMBEDDED WEB INTERFACES

Anton Scheibelmasser, Jürgen Menhart and Bernd Eichberger

Web-Technologies which came up in many fields of automation seem to be a solution which improves device integration in many ways. On the one hand the used Ethernet improves the installation techniques with reliable and approved network cables and routing devices. On the other hand the used internet protocols provide several services for the application software development. With the introduction of those services, the local controller of the measurement devices has to execute complex communication protocols in addition to the device specific tasks. This fact has serious influences on the measurement device instrumentation and the execution of the device firmware. Concerning new developments and compatible adaptations of existing instruments several ways for the integration of web technologies are available. The following article is intended to explain the architectural aspects of device integrations using Industrial Ethernet by means of an embedded web server. As a practical example to this architecture, concepts and results of a new developed communication module called EWI (embedded web interface) are given to demonstrate the improvements in measurement device integration in the field of automotive test bed automation.

MERGING OF ADVICES FROM MULTIPLE ADVISORY SYSTEMS - With Evaluation on Rolling Mill Data

Pavel Ettler, Josef Andrýsek, Václav Šmídl and Miroslav Kárný

The problem of evaluation of advisory system quality is studied. Specifically, 18 advisory strategies for operators of a cold rolling mill were designed using different modelling assumptions. Since some assumptions may be more appropriate in different working regimes, we also design a new advising strategy based on on-line merging of advices. In order to measure actual suitability of the advisory systems, we define two measures: operator’s performance index and coincidence of the observed operator’s actions with the advices. A time-variant model of advisory system suitability is proposed. Merging of the advices is achieved using Bayesian theory of decision-making. Final assessment of the original advisory systems and the new system is performed on data recorded during 6 months of operation of a real rolling mill. This task is complicated by the fact that the operator did not follow any of the advisory systems. Validation was thus performed with respect to the proposed measures. It was found that merging of the advising strategies can significantly improve quality of advising. The approach is general enough to be used in many similar problems.

MATHEMATICAL MODELLING OF THERMAL AREA IN CUTTING TOOL

Daschievici Luiza, Ghelase Daniela and Goanta Adrian

Since experimental researches regarding cutting process have stated a proportionality dependence of wear medium intensity on cutting area temperature and because this fact was avoid or ignored by thorough studies and researches, we considered to be helpful developing a physical-mathematical model able to correlate the two phenomena: wear and temperature in the cutting area. The complete and correct research on thermal phenomena in the cutting area is possible only by taking into consideration the feed-back relation between the physical and phenomenological elements of the studied tribosystem and also, by taking into account the splinter movement, resulting in a continuous supplying with cold layers of the splinter area and in heat evacuating by warm splinter movement.

A DISTRIBUTED FAULT TOLERANT POSITION CONTROL SYSTEM FOR A BOAT-LIKE INSPECTION ROBOT

Christoph Walter, Tino Krueger and Norbert Elkmann

Here we present the position control system of a swimming inspection robot for large under-ground con-crete pipes that are partially filled with waste water. The system consists of a laser-based measurement sub-system for position determination and a mechanical rudder to move the robot laterally within the pipe. The required software components are implemented as services following a CORBA-based architecture. To automatically adapt to different environment conditions a self tuning controller with hybrid requirements regarding latency and interarrival times of computed position values is used. We describe the architectural support for this type of application as well as how the system deals with ex-cessive latencies due to transient overload.

SMART SEMANTIC MIDDLEWARE FOR THE INTERNET OF THINGS

Artem Katasonov, Olena Kaykova, Oleksiy Khriyenko, Sergiy Nikitin and Vagan Terziyan

As ubiquitous systems become increasingly complex, traditional solutions to manage and control them reach their limits and pose a need for self-manageability. Also, heterogeneity of the ubiquitous components, standards, data formats, etc, creates significant obstacles for interoperability in such complex systems. The promising technologies to tackle these problems are the Semantic technologies, for interoperability, and the Agent technologies for management of complex systems. This paper describes our vision of a middleware for the Internet of Things, which will allow creation of self-managed complex systems, in particular industrial ones, consisting of distributed and heterogeneous components of different nature. We also present an analysis of issues to be resolved to realize such a middleware.

A GENETIC ALGORITHM APPLIED TO THE POWER SYSTEM RESTORATION PLANNING PROBLEM - A Metaheuristic Approach for a Large Combinatorial Problem

Adelmo Cechin, José Vicente Canto dos Santos, Arthur Tórgo Gómez and Carlos Mendel

This work reports the development of a Genetic Algorithm (GA) to solve the Power Systems Restoration Planning Problem (PSRP). The solution of the PSRP is a plan that informs to the Power System operator strategies or operation plans to be used after the occurrence of interruptions in the electrical energy transmission. The GA generates sequences of operations which are analyzed by a Power Flow program to verify and access their fitness. For this GA, a new genoma representation was developed, as well as two genetic operators, for crossover and mutation. This is one of the main contributions of this work. Tests performed with different electric networks shown the validity of the proposal.

FAIR AND EFFICIENT RESOURCE ALLOCATION - Bicriteria Models for Equitable Optimization

Włodzimierz Ogryczak

Resource allocation problems are concerned with the allocation of limited resources among competing activities so as to achieve the best performances. In systems which serve many users there is a need to respect some fairness rules while looking for the overall efficiency. The so-called Max-Min Fairness is widely used to meet these goals. However, allocating the resource to optimize the worst performance may cause a dramatic worsening of the overall system efficiency. Therefore, several other fair allocation schemes are searched and analyzed. In this paper we focus on mean-equity approaches which quantify the problem in a lucid form of two criteria: the mean outcome representing the overall efficiency and a scalar measure of inequality of outcomes to represent the equity (fairness) aspects. The mean-equity model is appealing to decision makers and allows a simple trade-off analysis. On the other hand, for typical dispersion indices used as inequality measures, the mean-equity approach may lead to inferior conclusions with respect to the outcomes maximization (system efficiency). Some inequality measures, however, can be combined with the mean itself into optimization criteria that remain in harmony with both inequality minimization and maximization of outcomes. In this paper we introduce general conditions for inequality measures sufficient to provide such an equitable consistency. We verify the conditions for the basic inequality measures thus showing how they can be used not leading to inferior distributions of system outcomes.

LOSS MINIMIZATION OF INDUCTION GENERATORS WITH ADAPTIVE FUZZY CONTROLLER

Durval de Almeida Souza*, José Antonio Dominguez Navarro** and Jesús Sallán Arasanz

In this paper a new technique for efficiency optimization of induction generator working a variable speed and load is introduced. The technique combines two distinct control methods, namely, on-line search of the optimal operating point, with a model based efficiency control. For a given operating condition, characterized by a given speed (m) and load torque (TL), the search control is implemented via the “Rosenbrock” method, which determines the flux level that results in the maximum output power. Once the optimal flux level has been found, this information is utilized to update the rule base of a fuzzy controller, which plays the role of an implicit mathematical model of the system. Initially, for any load condition the rule base yields the rated flux value. As the optimum points associated with the several operating conditions are identified, the rule base is progressively updated, such that the fuzzy controller learns to model the optimal operating conditions for the entire torque-speed plane. After every rule base update, the Rosenbrock controller output is reset, but it is kept active to track possible minor deviations of the optimum point.

LEARNING DISCRETE PROBABILISTIC MODELS FOR APPLICATION IN MULTIPLE FAULTS DETECTION

Luis E. Garza Castañón, Francisco J. Cantú Ortíz and Rubén Morales-Menéndez

We present a framework to detect faults in processes or systems based on probabilistic discrete models learned from data. Our work is based on a residual generation scheme, where the prediction of a model for process normal behavior is compared against measured process values. The residuals may indicate the presence of a fault. The model consists of a general statistical inference engine operating on discrete spaces, and represents the maximum entropy joint probability mass function (pmf) consistent with arbitrary lower order probabilities. The joint pmf is a rich model that, once learned, allows us to address inference tasks, which can be used for prediction applications. In our case the model allows the one step-ahead prediction of process variable, given its past values. The relevant dependencies between the forecast variable and past values are learnt by applying an algorithm to discover discrete bayesian network structures from data. The parameters of the statistical engine are also learn by an approximate method proposed by Yan and Miller. We show the performance of the prediction models and their application in power systems fault detection.

GPC AND NEURAL GENERALIZED PREDICTIVE CONTROL

S. Chidrawar, Nikhil Bidwai, L. Waghmare and B. M. Patre

As Model Predictive Control (MPC) relies on the predictive Control using a multilayer feed forward network as the plants linear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. This paper presents a detailed derivation of the Generalized Predictive Control and Neural Generalized Predictive Control with Newton-Raphson as minimization algorithm. Taking two separate systems tested the performances of the system. Simulation result show the effect of Neural network on Generalized Predictive Control. The performance comparison of these two-system configurations has been given in terms of ISE and IAE.

COGNITIVE TECHNICAL SYSTEMS IN A PRODUCTION ENVIRONMENT - Outline of a Possible Approach

Eckart Hauck, Arno Gramatke and Klaus Henning

High-Wage countries face the dilemmas of value- vs. planning orientation and the dilemma of economies of scale vs. economies of scope summed up in the term polylemma. To reduce the dilemma of planning vs. value orientation cognitive technical systems seem to be a promising approach. In this paper the requirements of such a cognitive system in a production environment is presented. Furthermore a first concept of a software architecture is given. To implement a knowledge base for a cognitive technical system certain formalism were scrutinized for their suitability in this approach and a possible use case for such a cognitive technical system is presented.

SELF CONSTRUCTING NEURAL NETWORK ROBOT CONTROLLER BASED ON ON-LINE TASK PERFORMANCE FEEDBACK

Andreas Huemer, Mario Gongora and David Elizondo

In this paper we present a novel methodology to create a powerful controller for robots that minimises the design effort. We show that using the feedback from the robot itself, the system can learn from experience. A method is presented where the interpretation of the sensory feedback is integrated in the creation of the controller, which is achieved by growing a spiking neural network system. The feedback is extracted from a performance measuring function provided at the task definition stage, which takes into consideration the robot actions without the need for external or manual analysis. With this research we aim to create a novel unsupervised design methodology for robot controllers where, starting with the interface between the sensors and actuators and the input and output neurons of a network, new connections are created using a novel structure tied to the performance interpretation of the robot. With this method we have enabled the neural network to optimise the total number of neurons and connections in the final system, creating an efficient learning controller. Results and conclusions are presented showing our contribution to further advance in the use of automated design as a tool for creating robotics control systems efficiently.

ONTOLOGY ADAPTER - Network Management System Interface Model

Lingli Meng, Lusheng Yan and Wenjing Li

This paper proposes a new way to define the interface model of network management system, that is ontology adapter. This model includes three parts, which are ontology agent, ontology knowledge base and ontology resource description. We can realize the uniform presentation of different network resource interface information using it. Therefore, we can take this model as a common data platform to offer the information to the network management system

STOCHASTIC CONTROL STRATEGIES AND ADAPTIVE CRITIC METHODS

Randa Herzallah and David Lowe

Adaptive critic methods have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, nonlinear and nonstationary environments. In this study, a novel probabilistic dual heuristic programming (DHP) based adaptive critic controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) adaptive critic method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterized by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the critic network is then calculated and shown to be equal to the analytically derived correct value.

LIGHT-WEIGHT REINFORCEMENT LEARNING WITH FUNCTION APPROXIMATION FOR REAL-LIFE CONTROL TASKS

Kary Främling

Despite the impressive achievements of reinforcement learning (RL) in playing Backgammon already in the beginning of the 90's, hardly any successful real-world applications of RL have been reported since then. This could be due to the tendency of RL research to focus on discrete Markov Decision Processes that make it difficult to handle tasks with continuous-valued features. Another reason could be a tendency to develop continuously more complex mathematical RL models that are difficult to implement and operate. Both of these issues are addressed in this paper by using the gradient-descent Sarsa($\lambda$) method together with a Normalised Radial Basis Function neural net. The experimental results on three typical benchmark control tasks show that these methods outperform most previously reported results on these tasks, while remaining computationally feasible to implement even as embedded software. Therefore the presented results can serve as a reference both regarding learning performance and computational applicability of RL for real-life applications.

AN APPROACH FOR A KNOWLEDGE-BASED NC PROGRAMMING SYSTEM

Ulrich Berger, Ralf Kretzschmann and Jan Noack

There are existing significant deficiencies in the information flow and access along the NC (Numerical Control) process chain. The deficiencies are solved insufficient by introducing CAD/CAM systems and feature-oriented specification languages. In contrast to that the application of new production and new machining systems requires an intensive information exchange. The introduced approach enables the preparation for feature-based work plans with methods known from the graph theory as a knowledge-based NC programming system. Therefore the work plan will be mapped into a directed graph in a mathematically defined way. Now it is possible to use algorithms to find the shortest path and a Hamiltonian path inside this directed graph regarding to given requirements. Thus, the work plan will be re-ordered and scheduled. Finally the corresponding NC paths will be generated and distributed to the machinery. Thence in this in-process paper the requirements, the investigation and selection of suitable knowledge structuring concepts, mathematically basics and the work flow in such a system will be pointed out. Finally a preliminary prototype will be introduced.

ADAPTIVE RESOURCES CONSUMPTION IN A DYNAMIC AND UNCERTAIN ENVIRONMENT - An Autonomous Rover Control Technique using Progressive Processing

Simon Le Gloannec, Abdel Illah Mouaddib and François Charpillet

This paper address the problem of an autonomous rover that have limited consumable resources to accomplish a mission. The robot has to cope with limited resources : it must decide the resource among to spent at each mission step. The resource consumption is also uncertain. Progressive processing is a meta level reasoning model particulary adapted for this kind of mission. Previous works have shown how to obtain an optimal resource consumption policy using a Markov decision process (MDP). Here, we make the assumption that the mission can dynamically change during execution time. Therefore, the agent must adapt to the current situation, in order to save resources for the most interesting future tasks. Because of the dynamic environment, the agent cannot calculate a new optimal policy online. However, it is possible to compute an approximate value function with which the robot will behave as good as if it knew the optimal policy.

FLEXIBLE ROBOT-BASED INLINE QUALITY MONITORING USING PICTURE-GIVING SENSORS

Chen-Ko Sung, Andreas Jacubasch and Thomas Müller

As part of the ROBOSENS project, the IITB developed and tested a new four-step concept for multiple sensor quality monitoring. The robot-based system uses an array of test-specific short-range and wide-range sensors which make the inspection process more flexible and problem-specific. To test this innovative inline quality monitoring concept and to adapt it to customized tasks, a development and demonstration platform was created. It consists of an industrial robot with various sensor ports - a so-called “sensor magazine” - with various task-specific, interchangeable sensors and a flexible transport system.

AN EFFICIENT INFORMATION EXCHANGE STRATEGY IN A DISTRIBUTED COMPUTING SYSTEM - Application to the CARP

Kamel Belkhelladi, Pierre Chauvet and Arnaud Schaal

Distributed computation models have been widely used to enhance the performance of traditional evolutionary algorithms, and they have been implemented on parallel computers to speed up the computation. In this paper, we introduce a multi-agent model conceived as a conceptual and practical framework for distributed genetic algorithms used both to reduce execution time and get closer to optimal solutions. Instead of using expensive parallel computing facilities, our distributed model is implemented on easily available networked PCs. Furthermore, distributed genetic algorithms with multiple subpopulations are difficult to configure because they are controlled by many parameters that affect their efficiency and accuracy. Among other things, one must decide the number and the size of the subpopulations (demes), the rate of migration, the frequency of migrations, and the destination of the migrants. Moreover, we develop an efficient information exchange strategy based on the different dynamic migration window methods defined in (Kim, 2002) and the selective migration model defined in (Eldos, 2006). To evaluate the proposed approach, different kinds of experiments have been conducted on an extended set of Capacitated Arc Routing Problem(CARP). Obtained results are useful for optimization practitioners and show the efficiency of our approach.

A MARINE FAULTS TOLERANT CONTROL SYSTEM BASED ON INTELLIGENT MULTI-AGENTS

Tianhao Tang and Gang Yao

This paper presents a hybrid intelligent multi-agent method for marine faults tolerant control (FTC). A new FTC schema, implemented by different kinds of agent, is discussed as well as the structure and functions of those agents, which have been encapsulated with intelligent algorithms to carry out different aspects in FTC. These agents could, having a purpose of trying to earn payoff as much as possible in a mission, communicate and form a coalition via negotiation when they find cooperation would bring them more benefits. Simulation experiments and its results are shown at last to demonstrate the efficiency of the proposed system.

EXPONENTIAL OBSERVER FOR A CLASS OF NONLINEAR DISTRIBUTED PARAMETER SYSTEMS WITH APPLICATION TO A NONISOTHERMAL TUBULAR REACTOR

Nadia Barje, Mohammed Achhab and Vincent Wertz

This paper present sufficient conditions to guarantee the existence of an exponential state estimator for a class of infinite dimensional non-linear systems driven in a real Hilbert state description. The theory is applied to a nonisothermal plug flow tubular reactor, governed by hyperbolic first order partial differential equations. For this application performance issues of the exponential state estimator design are illustrated in a simulation study.

NEURAL NETWORK AND GENETIC ALGORITHMS FOR COMPOSITION ESTIMATION AND CONTROL OF A HIGH PURITY DISTILLATION COLUMN

J. Fernandez de Cañete, P. del Saz-Orozco and S. Gonzalez-Perez

Many industrial processes are difficult to control because the product quality cannot be measured rapidly and reliably. One solution to this problem is neural network based control, which uses an inferential estimator (software sensor) to infer primary process outputs from secondary measurements, and control these outputs. This paper proposes the use of adaptive neural networks applied both to the prediction of product composition from temperature measurements, and to the dual control of distillate and bottom composition for a continuous high purity distillation column. Genetic algorithms are used to automatically choice of the optimum control law based on the neural network model of the plant. The results obtained have shown the proposed method gives better or equal performances over other methods such fuzzy, or adaptive control

RECONFIGURATION OF EMBEDDED SYSTEMS

Mohamed Khalgui, Martin Hirsch, Dirk Missal and Hans-Michael Hanisch

This paper deals with automatic reconfiguration of control systems following the component-based standard IEC61499. First of all, we propose a new reconfiguration semantic allowing to improve the system performance even if there is no hardware fault. In addition, we propose to characterize the possible reconfiguration forms in order to cover all the possible execution scenarios. To apply an automatic reconfiguration, we define thereafter an agent-based architecture that we propose to model with nested state machines to control the design complexity.

OBDD COMPRESSION OF NUMERICAL CONTROLLERS

Giuseppe Della Penna, Nadia Lauri, Daniele Magazzeni and Benedetto Intrigila

In the last years, the use of control systems has become very common, especially in the embedded systems contained in a growing number of everyday products. Therefore, the problem of the automatic synthesis of control systems is extremely important. However, most of the current techniques for the automatic generation of controllers, such as cell-to-cell mapping, dynamic programming, set oriented approach or model checking, typically generate numerical controllers that cannot be embedded in limited hardware devices due to their size. A possible solution to this problem is to compress the controller. However, most of the common lossless compression algorithms, such as LZ77, would decrease the controller performances due to their decompression overhead. In this paper we propose a new, completely automatic OBDD-based compression technique that is capable of reducing the size of any numerical controller up to a space savings of 90% without any noticeable decrease in the controller performances.

THE PARALLELIZATION OF MONTE-CARLO PLANNING - Parallelization of MC-Planning

S. Gelly, J. B. Hoock, A. Rimmel, O. Teytaud and Y. Kalemkarian

Since their impressive successes in various areas of large-scale parallelization, recent techniques like UCT and other Monte-Carlo planning variants have been extensively studied. We here propose and compare various forms of parallelization of bandit-based tree-search, in particular for our computer-go algorithm XYZ.

PATH PLANNING FOR MULTIPLE FEATURES BASED LOCALIZATION

Francis Celeste, Frederic Dambreville and Jean-Pierre Le Cadre

In surveillance or exploration mission in a known environment, the localization of the dedicated sensor is of main importance. In this paper, we discuss the path planning problem for the localization algorithm which correlates range and bearing measurements and a map composed of several features. The sensor motion is designed from an in information measure deduced from the Fisher Information Matrix. It is shown that a closed form expression of the cost can be obtained. The optimal features location can be neatly geometrically interpreted. An integral cost which includes the sensor perception is then formulated based on this information metric. It is used in a dynamic programming framework to tackle the path optimization problem.

AN ONLINE BANDWIDTH SCHEDULING ALGORITHM FOR DISTRIBUTED CONTROL SYSTEMS WITH MULTIRATE CONTROL LOOPS

Saroja Kanchi and Juan Pimentel

In this paper, we present an online scheduling algorithm for communication in a distributed control system. The packet size of the communication varies for each execution of the loop within certain bounds. We consider systems with closed loops that restart immediately after the completion of an execution. Our algorithm is based on priority of the loop and size of the communication packet. We demonstrate through simulation that our algorithm generates a feasible schedule that minimizes average control delay over all the loops. Our simulations demonstrate that this online schedule reduces average delay significantly compared to a-priori schedules for distributed control systems. We demonstrate that bandwidth utilization is more efficient in case of online scheduling.

COMBINATION OF BREEDING SWARM OPTIMIZATION AND BACKPROPAGATION ALGORITHM FOR TRAINING RECURRENT FUZZY NEURAL NETWORK

Soheil Bahrampour, Sahand Ghorbanpour and Amin Ramezani

The usage of recurrent fuzzy neural network has been increased recently. These networks can approximate the behaviour of the dynamical systems because of their feedback structure. The Backpropagation of error has usually been used for training this network. In this paper, a novel approach for learning the parameters of RFNN is proposed using combination of the backpropagation and breeding particle swarm optimization. A comparison of this approach with previous methods is also made to demonstrate the effectiveness of this algorithm. Particle swarm is a derivative free, globally optimizing approach that makes the training of the network easier. These can solve the problems of gradient based method, which are instability, local minima and complexity of taking derivation.

TWO-SIDED ASSEMBLY LINE - Estimation of Final Results

Waldemar Grzechca

The paper considers simple assembly line balancing problem and two-sided assembly line structure. In the last four decades a large variety of heuristic and exact solutions procedures have been proposed to balance one-sided assembly line in the literature. Some heuristic were given to balance two-sided lines, too. Some measures of solution quality have appeared in line balancing literature: balance delay (BD), line efficiency (LE), line time (LT) and smoothness index (SI). These measures are very important for estimation the balance solution quality. Author of this paper modified and discussed the line time and smoothness for two-sided assembly line. Some problems, which appeared during evaluations, are mentioned.

A REAL TIME EXPERT SYSTEM FOR FAULTS IDENTIFICATION IN ROTARY RAILCAR DUMPERS

Osevaldo S. Farias, Jorge H. M. Santos, João V. F. Neto, Sofiane Labidi, Thiago Drumond, José Pinheiro de Moura and Simone C. F. Neves

This paper describes the development of a real-time Expert System applied to the ore extraction Industrial branch, specifically used to assist the decision making and fault identification on rotary railcar dumpers of the operational productive system located at Ponta da Madeira Dock Terminal, built and operated by Companhia Vale do Rio Doce (CVRD) in São Luis-MA. The Expert System is built on JESS (Java Expert System Shell) platform and provides support to engineers and operators during the ore unloading as soon as supplying on-line information about faults triggered by device sensors of the rotary railcar. The system’s conception involves the application of CommonKADS methodology, knowledge engineering and artificial intelligence techniques at the symbolic level for representing and organizing the knowledge domain in which the system is applied.

AUTOMATIC PARAMETERIZATION FOR EXPEDITIOUS MODELLING OF VIRTUAL URBAN ENVIRONMENTS - A New Hybrid Metaheuristic

Filipe Cruz, António Coelho and Luis Paulo Reis

Expeditious modelling of virtual urban environments consists of generating realistic 3d models from limited information. It has several practical applications but typically suffers from a lack of accuracy in the parameter values that feed the modeller. By gathering small amounts of information about certain key urban areas, it becomes possible to feed a system that automatically compares and adjusts the input parameter values to find optimal solutions of parameter combinations that resemble the real life model. These correctly parameterized rules can then be reapplied to generate virtual models of real areas with similar characteristics to the referenced area. Based on several nature inspired metaheuristic algorithms such as genetic algorithms, simulated annealing and harmony search, this paper presents a new hybrid metaheuristic algorithm aiming to find the optimal solution of a multi-parameter real-based optimization problem. Results achieved in a simple test-case are also presented showing the potential of the new hybrid metaheuristic algorithm when compared with standard optimization algorithms.

WISA - A Modular and Hybrid Expert System for Machine and Plant Diagnosis

Mario Thron, Thomas Bangemann and Nico Suchold

Expert systems are well known tools for diagnosis purposes in medicine and industry. One problem is the hard efford, to create the knowledge base. This article describes an expert system for industrial diagnosis and shows an efficient approach for the creation of the rule base, which is based on the reusage of knowledge modules. These knowledge modules are representants for assets like devices, machines and plants. The article encourages manufacturers of such assets to provide diagnosis knowledge bases by using a proposed multi-paradigm rule definition language called HLD (Hybrid Logic Description). Rule based knowledge may be expressed by using various methodologies, which differ in expressiveness but also in runtime performance. The HLD allowes rules to be defined as propositional logic with or without the use of certainty factors, as Fuzzy Logic or as probabilistic rules as in Bayesian Networks. The most effective rule type may be choosen to describe causal dependencies between symptoms and faillures. An evaluation prototype implementation provides separate terminals for experts and operators to communicate with the HLD interpreter via Internet-based communication systems.

AN EVOLUTIONARY ALGORITHM FOR UNICAST/ MULTICAST TRAFFIC ENGINEERING

Miguel Rocha, Pedro Sousa, Paulo Cortez and Miguel Rio

A number of Traffic Engineering (TE) approaches have been recently proposed to improve the performance of network routing protocols, both developed over MPLS and intra-domain protocols such as OSPF. In this work, a TE approach is proposed for routing optimization in scenarios where unicast and multicast demands are simultaneously present. Evolutionary Algorithms are used as the optimization engine with overall network congestion as the objective function. The optimization aim is to reach a set of (near-)optimal weights to configure the OSPF protocol. The results show that the method is able to obtain networks with low congestion, even under scenarios with heavy unicast/multicast demands.

COLLISION AVOIDANCE SYSTEM PRORETA - Strategies Trajectory Control and Test Drives

R. Isermann, U. Stählin and M. Schorn

Methods and experimental results of a collision avoidance driver assistance system are described with automatic object detection, trajectory prediction, and path following with controlled braking and steering. The objects are detected by a fusion of LIDAR scanning and video camera pictures resulting in the location, size and speed of objects in front of the car. A desired trajectory is calculated depending on the distance, the width of a swerving action and difference speed. For the trajectory control different control methods were designed and tested experimentally like velocity depend linear feedback and feedforward control, nonlinear asymptotic output tracking and nonlinear flatness based control using extended one-track models with vehicle state estimation for the sideslip angle and cornering stiffness. Automatic braking is realized with an electrohydraulic brake (EHB) and automatic steering with an active front steering (AFS). The various control systems are compared by simulations and real test drives showing the behaviour of a VW Golf with automatic braking or/and automatic swerving to a free track, such avoiding hitting a suddenly appearing obstacle. The research project PRORETA was a four-years-cooperation between Continental Automotive Systems and Darmstadt University of Technology.

EVALUATION OF NEURAL PDF CONTROL STRATEGY APPLIED TO A NONLINEAR MODEL OF A PUMPED – STORAGE HYDROELECTRIC POWER STATION

G. A. Munoz-Hernandez, C. A. Gracios-Marin, A. Diaz-Sanchez, S. P. Mansoor and D. I. Jones

In this paper, a neural Pseudoderivative control (PDF) is applied to a nonlinear mathematical model of the Dinorwig pumped - storage hydroelectric power station. The response of the system with this auto-tuning controller is compared with the classic controller, currently implemented on the system. The results show how the application of PDF control to a hydroelectric pumped-storage station improves the dynamic response of the power plant, even when multivariable effects are taken into account.

THE BEES ALGORITHM AND MECHANICAL DESIGN OPTIMISATION

D. T. Pham, M. Castellani, M. Sholedol and A. Ghanbarzadeh

The Bees Algorithm is a search procedure inspired by the way honey-bees forage for food. A standard mechanical design problem, the design of a welded beam structure, was used to benchmark the Bees Algorithm against other optimisation techniques. The paper presents the results obtained showing the robust performance of the Bees Algorithm.

A NOVEL PARTICLE SWARM OPTIMIZATION APPROACH FOR MULTIOBJECTIVE FLEXIBLE JOB SHOP SCHEDULING PROBLEM

Souad Mekni, Besma Fayech Char and Mekki Ksouri

Because of the intractable nature of the problem of flexible job shop scheduling and its importance in both fields of production management and combinatorial optimization, it is desirable to employ efficient metaheuristics in order to obtain a better solution quality for the problem. In this paper, a novel approach based on the vector evaluated particle swarm optimization and the weighted average ranking is presented to solve flexible job shop scheduling problem (FJSP) with three objectives (i) minimize the makespan, (ii) minimize the total workload of machines and (iii) minimize the workload of critical machine. To convert the continuous position values to the discrete job sequences, we used the heuristic rule the Smallest Position Value (SPV). Experimental results in this work are very enouraging since that relevent solutions were provided in a reasonable computational time.

RFID BASED LOCATION IN CLOSED ROOMS - Implementation of a Location Algorithm using a Passive UHF-RFID System

Christoph Schönegger, Burkhard Stadlmann and Michael E. Wernle

This paper presents a new concept for determining the location of an RFID-tag without any additional hardware. For this positioning system standard RFID components within the UHF range are used. The measurement is based on a location algorithm which makes use of the RSSI value of the UHF reader. The RSSI value is the return signal strength indicator and, as it is shown in the paper in hand, this signal correlates to the distance between the RFID tag and the antenna of the reader. This positioning system is especially useful indoors, where other positioning systems may not work. For this reason it could prove very useful in various logistics applications. The maximum distance from antenna to the tag is approximately between 0.5 m and 3 m. To this end a special algorithm is used to obtain stable calculation results. A minimum of two antennas is needed to get a two-dimensional location.

PARALLEL MACHINE EARLINESS-TARDINESS SCHEDULING - Comparison of Two Metaheuristic Approaches

Marcin Bazyluk, Leszek Koszalka and Keith J. Burnham

This paper considers the problem of parallel machine scheduling with the earliness and tardiness penalties (PMSP\_E/T) in which a set of sequence-independent jobs is to be scheduled on a set of given machines to minimize a sum of the weighted earliness and tardiness values. The weights and due dates of the jobs are distinct positive numbers. The machines are diverse - each has a different execution speed of the respective jobs, thus the problem becomes more complex. To handle this, it two heuristics are employed, namely: the genetic algorithm with the MCUOX crossover operator and the tabu search. The performances of the both approaches are evaluated and their dependency on the shape of the investigated instances examined. The results indicate the significant predominance of the genetic approach for the larger-sized instances.

SENSOR AND ACTUATOR FAULT ANALYSIS IN ACTIVE SUSPENSION IN VIEW OF FAULT-TOLERANT CONTROL

Claudio Urrea and Marcela Jamett

This paper shows the first step of a fault tolerant control system (FTCS) to control active suspension on a full-car suspension model. In this paper, the elimination of the inevitable pitch and roll actions of a spring suspension between each axle and the body of a vehicle is studied. An actuator (linear motor) producing an electromagnetic force and a pneumatic force acting simultaneously on the same output element is used. This linear motor acts as a force generator that compensates instantly for the disturbing effects of the road surface. Simulation results to illustrate the system’s performance in front of the occurrence of sensor and actuator faults are shown.

HUNTER – HYBRID UNIFIED TRACKING ENVIRONMENT - Real-time Identification and Tracking System using RFID Technology

A. G. Foina and F. J. Ramirez Fernandez

This article presents the results of the use of RFID technology for trucks’ cargo real-time tracking. RFID tags were settled at trucks’ dump-carts and readers were spread throughout warehouses entrances, at the truck weighting scale and through unload platforms. The unload inspectors used robust PDA with camera, along with Wi-Fi access points installed in warehouses, to confirm the truck information and take a snapshot for future audits. A wireless broadband link was used to connect two weighting scale that are distant from the unloading area. All technologies communicate with a web-based middleware that manages all different devices. The system design is flexible enough to be used in very different applications like product process control, automated manufactory lines control, supply chain applications and others.

GENETIC-ALGORITHM SEEDING OF IDIOTYPIC NETWORKS FOR MOBILE-ROBOT NAVIGATION

Amanda M. Whitbrook, Uwe Aickelin and Jonathan M. Garibaldi

Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jerne’s idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, pre-engineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.

ROBOT GOES BACK HOME DESPITE ALL THE PEOPLE

Paloma de la Puente, Diego Rodriguez-Losada, Luis Pedraza and Fernando Matia

We have developed a navigation system for a mobile robot that enables it to autonomously return to a start point after completing a route. It works efficiently even in complex, low structured and populated indoor environments. A point-based map of the environment is built as the robot explores new areas; it is employed for localization and obstacle avoidance. Points corresponding to dynamical objects are removed from the map so that they do not affect navigation in a wrong way. The algorithms and results we deem more relevant are explained in the paper.

IDENTIFICATION OF THE DYNAMIC PRAMETERS OF THE C5 PARALLEL ROBOT

B. Achili, B. Daachi, Y. Amirat and A. Ali-Cherif

This paper deals with the experimental identification of the dynamic parameters of the C5 parallel robot. The inverse dynamic model of the robot is formulated under the form of linear equation with respect to the dynamic parameters. Moreover, a heuristic procedure for finding the exciting trajectory has been conducted. This trajectory is based on Fourier series whose coefficients are determined by using a heuristic method. The least squares method has been applied to solve an over-determined linear system which is obtained by sampling the dynamic model along the exciting trajectory. The experimental results show the effectiveness of the identification procedure.

ROBUST CONTROL OF THE C5 PARALLEL ROBOT

B. Achili, B. Daachi, A. Aliu-Cherif and Y. Amirat

This paper deals with the dynamic control of a parallel robot with C5 joints. Computed torque control and robust control have been studied and implemented. For this purpose, we have used the inverse dynamic model whose parameters have been experimentally identified. The closed loop stability has been studied using the Lyapunov principle. The addition of a robustness term based on sliding mode technique ensures good tracking performances. The experimental results show the effectiveness of the robust control.

ROBOT NAVIGATION MODALITIES

Ray Jarvis

Whilst navigation (robotic or otherwise) consists simply of traversing from a starting point to a goal, there are a plethora of conditions, states of knowledge and functional intentions which dictate how best to execute this process in a manageable, reliable, safe and efficient way. This position paper addresses the broad issues of how a continuum of choices from pure manual or teleoperation control through to fully autonomous operation can be laid out and then selected from, taking into account the variety of factors listed above and the richness of live sensory data available to describe the operational environment and the location of the robot vehicle within it.

SHOE GRINDING CELL USING VIRTUAL MECHANISM APPROACH

Bojan Nemec and Leon Zlajpah

The paper describes the automation of the shoe grinding process using an industrial robot. One of the major problems of flexible automation using industrial robots is how to avoid joint limitations, singular configuration and obstacles. This problem can be solved using kinematically redundant robots. Due to the circular shape of the grinding disc, the robot becomes kinematically redundant. This task redundancy was efficiently handled using virtual mechanism approach, where the tool is described as a serial mechanism.

ROBOTIC WHEELCHAIR CONTROL CONSIDERING USER COMFORT - Modeling and Experimental Evaluation

Razvan Solea and Urbano Nunes

This paper analyzes the comfort of wheelchair users when a sliding mode trajectory-tracking controller is used. The transmission of the horizontal (fore-and-aft) vibration to the head-neck complex (HNC) in the seated human body may cause unacceptable discomfort and motion sickness. A double-inverted pendulum model with two degrees of freedom is considered as a model for the HNC. The user comfort is examined not only in the time domain (using the fourth power vibration dose value), but also in the frequency domain (using the cross-spectral density method). For measuring the acceleration of the wheelchair, along the trajectory, an inertial measurement unit was used.

DYNAMICAL MODELS FOR OMNI-DIRECTIONAL ROBOTS WITH 3 AND 4 WHEELS

Hélder P. Oliveira, Armando J. Sousa, A. Paulo Moreira and Paulo J. Costa

Omni-directional robots are becoming more and more common in recent robotic applications. They offer improved ease of maneuverability and effectiveness at the expense of increased complexity. Frequent applications include but are not limited to robotic competitions and service robotics. The goal of this work is find a precise dynamical model to predict the robot behavior. During this work, models were found for two real world omni-directional robot configurations and its parameters estimated using a prototype that can have 3 or 4 wheels. Results of experimental runs are presented in order to validate the presented work.

REAL TIME GRASPING OF FREELY PLACED CYLINDRICAL OBJECTS

Mario Richtsfeld, Wolfgang Ponweiser and Markus Vincze

In the near future, service robots will support people with different handicaps to improve the quality of their life. One of the required key technologies is to setup the grasping ability of the robot. This includes an autonomous object detection and grasp motion planning to fulfil the task of providing objects from any position on a table to the user. This paper presents a complete system, which consists of a fixed working station equipped with a laser-range scanner, a seven degrees of freedom arm manipulator and an arm prothesis as gripper. The contribution of this work is to use only one sensor system based on a laser-range scanning head to solve this challenge. The presented work is tested at a live demo presentation in front of more than 1000 college students in about 50 trials. The goal is that the user can select any defined object on the table and the robot arm delivers it to a target position or to the disabled person.

DIAGNOSIS OF DISCRETE EVENT SYSTEMS WITH PETRI NETS AND CODING THEORY

Dimitri Lefebvre

Event sequences estimation is an important issue for fault diagnosis of DES, so far as fault events cannot be directly measured. This work is about event sequences estimation with Petri net models. Events are assumed to be represented with transitions and firing sequences are estimated from measurements of the marking variation. Estimation with and without measurement errors are discussed in n – dimensional vector space over alphabet Z3 = {-1, 0, 1}. Sufficient conditions and estimation algorithms are provided. Performance is evaluated and the efficiency of the approach is illustrated on two examples from manufacturing engineering.

MODELING AND SIMULATION OF A NEW PARALLEL ROBOT USED IN MINIMALLY INVASIVE SURGERY

Doina Pisla, Calin Vaida, Nicolae Plitea, Jürgen Hesselbach, Annika Raatz, Marc Simnofske, Arne Burisch and Liviu Vlad

Surgery is one of the fields where robots have been introduced due to their positioning accuracy which exceed the human capabilities. Parallel robots offer higher stiffness and smaller mobile mass than serial ones, thus allowing faster and more precise manipulations that fit medical applications. In the paper is presented the modeling and simulation of a new parallel robot used in minimally invasive surgery. The parallel architecture has been chosen for its superiority in precision, repeatability, stiffness, higher speeds and occupied volume. The robot kinematics, singular position identification and workspace generation are illustrated. Using the developed virtual model of the parallel robot, some simulation tests are presented. The latest obtained results demonstrate that the computing time necessary for generating the virtual model is relatively small.

DYNAMIC MODELING OF A 6-DOF PARALLEL STRUCTURE DESTINATED TO HELICOPTER FLIGHT SIMULATION

Nicolae Plitea, Adrian Pisla, Doina Pisla and Bogdan Prodan

The dynamic analysis is the basic element of the mechanical design and control of parallel mechanisms. The parallel robots dynamics requires a great deal of computing as regards the formulation of the generally nonlinear equations of motion and their solution. In this paper a solution for solving the dynamical model of a 6-DOF parallel structure destined to helicopter flight simulation is presented. The obtained dynamical algorithms, based on the kinematical ones, offer the possibility of a complex study for this type of parallel structure in order to evaluate the dynamic capabilities and to generate the control algorithms.

RACBOT-RT: ROBUST DIGITAL CONTROL FOR DIFFERENTIAL SOCCER-PLAYER ROBOTS

João Monteiro and Rui Rocha

Robot soccer is a popular testbed to study challenging problems of mobile robotics. It is recognized in the robot soccer domain that robust trajectory control and high responsiveness to motion commands are key aspects to successfully deal with the game dynamic. With this aim, the paper presents a digital controller developed to small-sized robot soccer players. A special emphasis has been given to design a controller as much generic as possible, which can be applied to any mobile robot with differential kinematics. The theoretical framework is based on Lyapunov equations for pose stability convergence. The controller was implemented as a software module running on the robot, which responds to motion commands through the decomposition of the trajectory into a set of virtual reference positions with respect to the world reference coordinates system, which are further followed robustly by the robot, even in the presence of unwanted motion disturbances. Experimental results obtained with a mobile robot moving on the game field demonstrate the quality of the proposed solution and validate the implemented controller.

CONTRIBUTION CONCERNING ROBOT ACCURACY USING NUMERICAL MODELING

Daniela Ghelase, Luiza Daschievici and Irina Ghelase

The kinematical accuracy of robot is very important. It is induced by the rigidity of each mechanism of the robot. The paper presents a numerical method to evaluate the rigidity of worm-gearing teeth. The software, including setting-up and graphic display, could be adopted of any kind of cylindrical worm-gear drive or for spur gear drives and bevel gear drives, mechanisms which are in the robot structure. Besides, we can determine geometrical parameters of the gear drives which influence the increase of accuracy of robot linkages.

HYDROGEN POWERED CAR CONTROL SYSTEM

Srovnal Vilem, Koziorek Jiri, Horak Bohumil, Adam George and Garani Georgia

Mobile embedded systems belong among the typical applications of the distributed systems control in real time. An example of a mobile control system is the hydrogen powered prototype car control system. The proposal and realization of such distributed control system represents a demanding and complex task of real time control for track optimizing with minimal fuel consumption. Design and realization of distributed control system, mention above, is prepared to realize as a complex laboratory task. Control system software using of multi-agent technology with dynamic mutual negotiation of mobile system parts. This task allows in a form of control system for prototype race car modelling of distributed control system. The real hardware and software model is also important motivation for extended study.

PROGRESSIVE MESH BASED ITERATIVE CLOSEST POINTS FOR ROBOTIC BIN PICKING

Kay Boehnke and Marius Otesteanu

This paper describes a hierarchical registration process using the iterative closest point algorithm combined with a Progressive mesh. We integrated this in a system for automated robotic bin picking. Laser range sensors provide range data of a box filled with scrambled production parts. An industrial robot is use to pick these parts out of the box and feed them into an automated process. To find the exact pose of the objects we use knowledge about the form of the objects to find them in range data. We simulate the appearance of object poses and compare them with the real range data provided by laser range sensors. The coarse pose is estimated in a first step und then refined with the well known iterative Closest Point (ICP) algorithm combined with Progressive meshs for hierarchical object localization. We evaluate our approach with different test scenarios and show the comprehensive potential of this idea for other registration problems.

VIDEO TRANSMISSION WITH ADAPTIVE QUALITY BASED ON NETWORK FEEDBACK FOR MOBILE ROBOT TELEOPERATION IN WIRELESS MULTI-HOP NETWORKS

Florian Zeiger, Markus Sauer and Klaus Schilling

A video stream is still one of the most important data sources for the user while remote-operating a mobile robot. Human operators have comprehensive capabilities to interpret the displayed image information, but therefore, some constraints must be fulfilled. Constant frame rates and delays below a certain threshold are a minimum requirement to use video for teleoperation. Modern multi-hop networks often use WLAN to set up ad-hoc networks of mobile nodes with each node acting as traffic source, sink, or router. Considering these networks, routes between sources and destinations might be established via several relay nodes. Thus, the utilization of intermediate nodes which are part of a route influences the overall route performance, whereas sender and receiver have no direct feedback of the overall route status. In case video is transmitted via wireless ad-hoc networks in a teleoperation scenario, the displayed video-stream for the operator might have variable frame rates, very high packet loss, and packet inter-arrival times which are not appropriate for mobile robot teleoperation. This work presents an approach using a feedback generated by the network to adapt the image quality to present communication constraints. Thus, according to the current network status, the best possible video image is provided to the operator while keeping constant frame rates and low packet loss.

PARAMETER TUNING OF ROUTING PROTOCOLS TO IMPROVE THE PERFORMANCE OF MOBILE ROBOT TELEOPERATION VIA WIRELESS AD-HOC NETWORKS

Florian Zeiger, Nikolaus Kraemer and Klaus Schilling

Currently, the use of wireless networks is very common in the field of networked robotics and can be considered as a key issue for capable multi robot systems with a high grade of mobility. Nevertheless, this mobility requests for special features of the communication infrastructure, which leads to the integration of mobile robots into wireless ad-hoc networks. Since the late nineties, more than 80 ad-hoc routing protocols were developed and nowadays some of them are implemented and ready to use in real world applications. A comparison of four ad-hoc routing protocols (AODV, DSR, OLSR, and BATMAN) showed some shortfalls of the default parameter settings not allowing a reliable teleoperation of mobile robots while using AODV, OLSR, or BATMAN. This work is focused on the parameter tuning of the routing protocols to use them in wireless ad-hoc networks of mobile robots. The time required for route reestablishing, as well as the packet loss during rerouting is investigated in hardware tests of a network with dynamic network topology consisting of mobile robots. It could be demonstrated, that an appropriate parameter setting of OLSR and AODV allow the teleoperation of mobile robots in outdoor environments via a wireless ad-hoc network.

LegOSC - Mindstorms NXT Robotics Programming for Artists

Jorge Cardoso, Manuel Ferreira and Cristina Santos

Robotics is an interesting but difficult area for digital artists who generally don’t have much academic background on electronics or computer programming. Digital art students normally use high-level application to program their visual and sonorous installations. This paper presents LegOSC - a tool that allows the control of the Mindstorms NXT robots from any application that uses the Open Sound Control protocol which is implemented by most of those high-level applications. This allows artists to create works which incorporate robotic parts using the familiar programming environment.

ACTIVE SECURITY SYSTEM FOR AN INDUSTRIAL ROBOT BASED ON ARTIFICIAL VISION AND FUZZY LOGIC PRINCIPLES

B. Fevery, B. Wyns, L. Boullart, J. R. Llata García and C. Torre Ferrero

An active security system assures that interacting robots don’t collide or that a robot operating independently doesn’t hit any obstacle that is encountered in the robots workspace. In this paper, an active security system for a FANUC industrial robot is introduced. The active security problem where one robot needs to avoid a moving obstacle in its workspace is considered. An obstacle detection and localization mechanism based on stereoscopic vision methods was successfully developed. To connect the vision system, an operator’s pc and the robot environment a real-time communication is set up over Ethernet using socket messaging. We used fuzzy logic for intelligent trajectory planning. A multitask oriented robot application in the KAREL programming language of FANUC Robotics was implemented and tested.

A QUADRATIC PROGRAMMING APPROACH TO THE MINIMUM ENERGY PROBLEM OF A MOBILE ROBOT

Alain Segundo Potts, José Jaime da Cruz and Reinaldo Bernardi

As a consequence of physical constraints and of dynamical nonlinearities, optimal control problems involving mobile robots are generally difficult ones. Many algorithms have been developed to solve such problems, the more common being related to trajectory planning, minimum-time control or any specific performance index. Nevertheless optimal control problems associated to mobile robots have not been reported. Minimum energy problems subject to both equality and inequality constraints are generally intricate ones to be solved using classical methods. In this paper we present an algorithm to solve it using a Quadratic Programming approach. In order to illustrate the application of the algorithm, one practical problem was solved

WHAT’S THE BEST ROLE FOR A ROBOT? - Cybernetic Models of Existing and Proposed Human-Robot Interaction Structures

Victoria Groom

Robots intended for human-robot interaction are currently designed to fill simple roles, such as task completer or tool. The design emphasis remains on the robot and not the interaction, as designers have failed to recognize the influence of robots on human behavior. Cybernetic models are used to critique existing models and provide revised models of interaction that delineate the paths of social feedback generated by the robot. Proposed robot roles are modeled and evaluated. Features that need to be developed for robots to succeed in these roles are identified and the challenges of developing these features are discussed.

THE APPLICATION OF REFERENCE-PATH CONTROL TO VEHICLE PLATOONS

Drago Matko, Gregor Klančar, Sašo Blažič, Olivier Simonin, Franck Gechter, Jean-Michel Contet and Pablo Gruer

A new algorithm for the control of vehicle platooning is proposed and tested on a robot-soccer test bed. We considered decentralized platooning, i.e., a virtual train of vehicles, where each vehicle is autonomous and decides on its motion based on its own perceptions. The platooning vehicles have non-holonomic constraints. The following vehicle only has information about its own orientation and about its distance and azimuth to the leading vehicle. Its position is determined using odometry and a compass. The reference position and the orientation of the following vehicle are determined by the estimated path of the leading vehicle in a parametric polynominal form. The parameters of the polynominals are determined using the least-squares method. This parametric reference path is also used to determine the feed-forward part of the applied control algorithm. The feed-back control consists of a state controller with three inputs: the longitudinal and lateral position errors and the orientation error. The results of the experiments demonstrate the applicability of the proposed algorithm for vehicle platoons.

AN EMBEDDED SYSTEM FOR SMALL-SCALED AUTONOMOUS VEHICLES

David Vissière and Nicolas Petit

We consider the problem of designing a modular real-time embedded system for control applications with unmanned vehicles. We propose a simple and low-cost solution. Its computational power can be easily improved, depending on application requirements. To illustrate its performance, we report the implementation of a 75~Hz Extended Kalman Filter used for state estimation on a small-scaled helicopter.

WALKING PLANNING AND CONTROL FOR A BIPED ROBOT UPSTAIRS

Chenbo Yin, Donghua Zheng and Le Xiao

The focus of this paper is the problem of walking stability control in humanoid robot going upstairs. Walking stability is a very important problem in the field of robotics. Lots of researches have been done to get stable walking on plane. But it is very limited on going upstairs. We first plan the gate of ankle and hip when going upstairs as well as the calculation of stable region and stability margin. Then the emergency-coping strategy of enlarging the support polygon is provided. At last, a control system which is proved to be effective by simulation is presented. If the ZMP is in the support polygon, this control system makes fine setting to gait to get higher stability. If the ZMP is out of the support polygon, the control system adjusts the location of ZMP through the emergency coping strategy.

DRIVER’S DROWSINESS DETECTION BASED ON VISUAL INFORMATION

Marco Javier Flores, José María Armingol and Arturo de la Escalera

In this paper, a new Driver Assistance System (DAS) for automatic driver’s drowsiness detection based on visual information and image processing is presented. This algorithm works on several stages using Viola and Jones (VJ) object detector, expectation maximization algorithm, the Condensation algorithm and support vector machine to compute a drowsiness index. The goal of the system is to help in the reduction of traffic accidents caused by human errors. Examples of different driver’s images taken over a real vehicle are shown to validate the algorithm.

HYBRID MATCHING OF UNCALIBRATED OMNIDIRECTIONAL AND PERSPECTIVE IMAGES

Luis Puig, J. J. Guerrero and Peter Sturm

This work presents an automatic hybrid matching of central catadioptric and perspective images. It is based on the hybrid epipolar geometry. The goal is to obtain correspondences between an omnidirectional image and a conventional perspective image taken from different points of view. Mixing both kind of images has multiple applications in visual localization, recognition, surveillance and robot navigation, since an omnidirectional image captures many information and perspective images are the simplest way of acquisition. Scale invariant features with a simple unwrapping are considered to help the initial putative matching. Then a robust technique gives an estimation of the hybrid fundamental matrix, to avoid outliers. Experimental results with real image pairs show the feasibility of that hybrid and difficult matching problem.

TEMPORAL MATCH OF MULTIPLE SOURCE DATA IN AN ETHERNET BASED INDUSTRIAL ENVIRONMENT

Daniela Hossu and Andrei Hossu

The actual trend in automation control systems is to distribute control logic to modular and easy to connect production cells. As part of this trend is the increase of Ethernet technology for machine-machine data communication inside this modular based architecture. The paper presents a robotic handling application of moving parts located on a transport conveyor. Data representing a set of parameters of the parts to be handle form the conveyor is provided by a Routing Control System (RCS). The Control Management System (CMS), which controls a number of robotic cells is receiving this data from RCS and merge it with the information provided by an Artificial Vision System. The communication between these two Control Systems (RCS and CMS) is Ethernet-based. Ethernet technology is good, reliable and fast for large amount of data, but because of its non-deterministic character, it has a lack of tools for data synchronization. The paper includes an analysis of the experimental results of the measurements of the non-deterministic factor of the existing network. The "worst case scenario" of the maximum communication delay caused by Ethernet traffic and the minimum time between two consecutive data commands, shows that without recovering data transfer time-consistency, the application requirements can not be achieved. The paper is presenting a mechanism developed at protocol level, in order to guarantee the consistency in time, at CMS level, of the data provided from RCS with the data provided by Vision System.

A NEW APPROACH OF GRAY IMAGES BINARIZATION FOR ARTIFICIAL VISION SYSTEMS WITH THRESHOLD METHODS

Daniela Hossu and Andrei Hossu

The paper presents some aspects of the (gray level) image binarization methods used in artificial vision systems. It is introduced a new approach of gray level image binarization for artificial vision systems dedicated to industrial automation – temporal thresholding. In the first part of the paper are extracted some limitations of using the global optimum thresholding in gray level image binarization. In the second part of this paper are presented some aspects of the dynamic optimum thresholding method for gray level image binarization. Starting from classic methods of global and dynamic optimal thresholding of the gray level images in the next section are introduced the concepts of temporal histogram and temporal thresholding. In the final section are presented some practical aspects of the temporal thresholding method in artificial vision applications form the moving scene in robotic automation class; pointing out the influence of the acquisition frequency on the methods results.

CALIBRATION ASPECTS OF MULTIPLE LINE-SCAN VISION SYSTEM APPLICATION FOR PLANAR OBJECTS INSPECTION

Andrei Hossu and Daniela Hossu

Besides the accuracy performances and response time, one of the characteristics of an Industrial Vision System is its set-up time. Minimizing the set-up time while keeping the performances in accuracy is one of the goals of any advanced Vision System. The calibration method presented in the paper is developed for a dual line-scan camera system. The paper presents the architecture and the purpose and the performances required for the proposed Industrial Vision System. The calibration method presented is based on analyzing the image of a calibration tool exposed to the Vision System. There are presented the type of dimensional distortions identified from the experimental results. The second part of the paper presents the calibration method. The Industrial Vision System described in the paper is designed for silhouette inspection of planar objects located on a moving scene (transport conveyor), in a robotic handling application. This means the Vision System is not analyzing the volumetric characteristics of the objects. However the height of the object is varying in time (from one set of objects to another). Due to the fact the distance between the cameras and the objects is changing, the measuring results are affected. The proposed calibration method allow the Vision System to self adjust the calibration parameters for a known new height of the objects, without disturbing the application. In the final section of the paper are presented some practical aspects of how the results of the proposed calibration method require minimum computational efforts from the online tasks of the Vision System.

OPTIMISING A FLYING ROBOT - Controller Optimisation using a Genetic Algorithm on a Real-World Robot

Benjamin N. Passow and Mario Gongora

This work presents the optimisation of the heading controller of a small flying robot. A genetic algorithm (GA) has been used to tune the proportional, integral, and derivative (PID) parameters of the helicopter’s controller. Instead of evaluating each individual’s fitness in an artificial simulation, the actual flying robot has been used. The performance of a hand-tuned PID controller is compared to the GA-tuned controller. Tests on the helicopter confirm that the GA’s solutions result in a better controller performance. Further more, results suggest that evaluating the GA’s individuals on the real flying robot increases the controller’s robustness.

A PERCEPTUAL MOTOR CONTROL MODEL BASED ON OUTPUT FEEDBACK ADAPTIVE CONTROL THEORY

Hirofumi Ohtsuka, Koki Shibasato and Shigeyasu Kawaji

In this paper, a perceptual motor control model based on output feedback adaptive control theory is considered from the viewpoint of voluntary movement such as hand-tracking control. At first, we give an account of the basic theory of the output feedback control based on almost strict positive real characteristics for the linear plant and the Smith prediction method for plant with pure time delay. Then, a perceptual motor control model is constructed using together with above methods. In the proposed method, there exists the attractive structural similarity between the cerebrum-cerebellum neuro-motor signal feedback loop and the adaptive controller - compensators local minor feedback loop. The proposed perceptual motor control model is examined through the comparison of between the experiment and the simulation of for handling 1-link mechanism in order to track an indicator.

TWO LAYERS ACTION INTEGRATION FOR HRI - Action Integration with Attention Focusing for Interactive Robots

Yasser Mohammad and Toyoaki Nishida

\fontsize{9}{11}\selectfont Behavior architectures are widely used to program interactive robots. In these architectures multiple \emph{behaviors} are usually running concurrently so a mechanism for integrating the resulting actuation commands from these \emph{behaviors} into actual actuation commands sent to the robot's motor system must be faced. Different architectures proposed different action integration mechanisms that range from distributed to central integration. In this paper an analysis of the special requirements that HRI imposes on the action integration system is given. Based on this analysis a novelle hybrid action integration mechanism that combines distributed attention focusing with a fast central integration algorithm is presented in the framework of the EICA architecture. The proposed system was tested in a simulation of a listener robot that aimed to achieve human-like nonverbal listening behavior in real world interactions. The analysis of the system showed that the proposed mechanism can generate coherent human-like behavior while being robust against signal correlated noise.

TELECONTROL PLATFORM - Telecontrol Platform for Industrial Installations

Eduardo J. Moya, Oscar Calvo, José María Pérez, José Ramón Janeiro and David García

This article explains the telecontrol platform for industrial installations developed by CARTIF Foundation. Using this system it will be able to send control orders and receive notification of alarms from the PLC thanks to SMS messages (Short Messages System) which use GSM technology. In case of requiring a greater flow of data it will use telephone line combined with MODBUS protocol. All this will enable us to monitor and control any industrial installation with a very low cost

TRAFFIC SIGN RECOGNITION WITH CONSTELLATIONS OF VISUAL WORDS

Toon Goedemé

In this paper, we present a method for fast and robust object recognition. As an example, the method is applied to traffic sign recognition from a forward-looking camera in a car. To facilitate and optimise the implementation of this algorithm on an embedded platform containing parallel hardware, we developed a voting scheme for constellations of visual words, i.e. clustered local features (SURF in this case). On top of easy implementation and robust and fast performance, even with large databases, an extra advantage is that this method can handle multiple identical visual features in one model.

DCT DOMAIN VIDEO WATERMARKING - Attack Estimation and Capacity Evaluation

O. Dumitru, M. Mitrea and F. Prêteux

The first difficulty which should be overcome when trying to evaluate with accuracy the video watermarking capacity is the lack of a reliable statistical model for the malicious attacks. The present paper brings into evidence that the attack effects in the DCT (Discrete Cosine Transform) domain are stationary and computes the corresponding pdfs. In this respect, an in-depth statistical approach is deployed by combining Gaussian mixture estimation with the probability confidence limits. Further on, these pdfs are involved in capacity computation. The experimental results are obtained on a corpus of 10 video sequences (about 30 minutes each), with heterogeneous content (film, news, home, etc).

LEARNING BY EXAMPLE - Reinforcement Learning Techniques for Real Autonomous Underwater Cable Tracking

Andres El-Fakdi, Marc Carreras, Javier Antich and Alberto Ortiz

This paper proposes a field application of a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a Direct Policy Search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot $ICTINEU^{AUV}$.

MODIFIED LOCAL NAVIGATION STRATEGY FOR UNKNOWN ENVIRONMENT EXPLORATION

Safaa Amin, Andry Tanoto, Ulf Witkowski, Ulrich Rückert and Saied Abdel-Wahab

This paper presents an algorithm for unknown environment exploration. Our algorithm based on the local navigation algorithm (LNA) that we have described in a previous paper. The LNA doesn’t take into account the case in which the robots are trapped and stop exploring the environment. In this paper, we propose some modifications to overcome this problem and demonstrate it by using real robots. For validation purpose, we ran several experiments using mini-robot Khepera II running on the Teleworkbench. The complete environment is divided into small quadratic patches with some objects placed in it representing obstacles. With on-board infrared sensors and wheel encoder, the robot can successfully explore the unknown environment. Moreover, by calculating the distance to surrounding patches, the implemented algorithm will minimize the distance traveled, and in turn of consumed energy and time. This paper also shows the advantage of using the Teleworkbench for performing experiments using real robots.

REAL TIME TRACKING OF AN OMNIDIRECTIONAL ROBOT - An Extended Kalman Filter Approach

José Gonçalves, José Lima and Paulo Costa

This paper describes a robust localization system, similar to the used by the teams participating in the Robocup Small size league (SLL). The system, developed in Object Pascal, allows real time localization and control of an autonomous omnidirectional mobile robot. The localization algorithm is done resorting to odometry and global vision data fusion, applying an extended Kalman filter, being this method a standard approach for reducing the error in a least squares sense, using measurements from different sources

IMPLEMENTATION OF A HOMOGRAPHY-BASED VISUAL SERVO CONTROL USING A QUATERNION FORMULATION

T. Koenig and G. N. De Souza

In this paper, we present the implementation of a homography-based visual servo controller as introduced in [4]. In contrast to other visual servo controllers, this formulation uses a quaternion representation of the rotation. By doing so, potential singularities introduced by the rotational matrix representation can be avoided, which is usually a very desirable property in, for example, aerospace applications such as for visual control of satellites, helicopters, etc. The movement of the camera and the image processing were performed using a simulation of the real environment. This testing environment was developed in Matlab-Simulink and it allowed us to test the controller regardeless of the mechanism in which the camera was moved and the underlying controller that was needed for this movement. The final controller was tested using yet another simulation program provided by Kawasaki Japan for the UX150 industrial robot. The setup for testing and results of the simulations are presented in this paper.

ROBOT LOCALIZATION BASED ON VISUAL LANDMARKS

Hala Mousher Ebied, Ulf Witkowski, Ulrich Rückert and Mohamed Saied Abdel-Wahab

In this paper, we will consider the localization problem of the autonomous minirobot Khepera II in a known environment. Mobile robots must be able to determine their own position to operate successfully in any environments. Our system combines odometry and a 2-D vision sensor to determine the position of the robot based on a new triangulation algorithm. The new system uses different colored cylinder landmarks which are positioned at the corners of the environment. The main aim is to analyze the accuracy and the robustness in case of noisy data and to obtain an accurate method to estimate the robot’s position.

ALTITUDE CONTROL OF SMALL HELICOPTERS USING A PROTOTYPE TEST BED

Nikos I. Vitzilaios and Nikos C. Tsourveloudis

In this paper we present an experimental test bed for the development and evaluation of control systems for unmanned helicopters. The test bed consists of a small unmanned helicopter, mounted on a flying stand that permits all possible movements but prevents the helicopter from damaging or crashing. A fuzzy controller is developed in MATLAB and tested in the helicopter using the test bed. The controller is able to perform hovering and altitude control. Experimental results are presented for various test cases.

AN APPROACH TO OBTAIN A PLC PROGRAM FROM A DEVS MODEL

Hyeong T. Park, Kil Y. Seong, Suraj Dangol, Gi N. Wang and Sang C. Park

Proposed in the paper is an approach to generate the PLC code from the Discrete Event System Specification (DEVS) model. DEVS have been widely accepted to model the real system for the discrete event system simulation. The objective of this paper is to generate PLC control code from the DEVS model. To achieve it, this paper proposes two steps. First step is to convert the real system into the virtual model using the ‘three-phase modeling procedure’. In the second step, the obtained model is formalized with DEVS formalism. The final model consists of different components, among them the state manager and the flow controller model plays vital role to generate PLC code. In this paper, proposed steps are described with a work cell example.

COMPARATIVE STUDY OF ROBOT-DESIGNS FOR A HANDHELD MEDICAL ROBOT

Peter P. Pott, Markus L. R. Schwarz, Achim Wagner and Essameddin Badreddin

Robotic systems are used within a great variety of medical disciplines. A handheld robot promises a number of advantages compared to conventional (medical) robots but this approach leads to strict specifications regarding size, weight and dynamic properties. A new hybrid kinematics – the Epizactor – seems to be advantageous and is compared to two well-known parallel kinematics regarding the ratio of workspace and volume the number of kinematic elements, the cost of computation, the stiffness the effects of clearance, actuation (weight), and accuracy using a well-described industrial method for comparison. It becomes clear that the Epizactor has advantages concerning the ratio of workspace and volume, needs a smaller number of kinematic elements and fewer computations, and has less than half the mass than the parallel kinematics. Its accuracy, stiffness and the effects of clearance are comparable. The advantages of this new kinematic set-up lead to a first deployment within the field of medical robotics.

RE-USING 3D MODELING DATA FOR CONSTRUCTING 3D SIMIULATION DATA

Jonggeun Kwak, Min. S. Ko, Sang C. Park and Gi-Nam Wang

With the aid of the powerful computational ability and software tools, we undergo rapid change in a whole product manufacturing process. In a traditional way, it took long time and cost to build real manufacturing line. The behind time change for the manufacturing process ends up with supplementing large amount of budget. Therefore early detecting the errors on manufacturing process saves quite a big amount of time and money. As a result, the need for plant simulations rises. When we simulate manufacturing line on a virtual environment, it is not easy to acquire 3D data. If we have 3D CAD data, we can reuse them for each tools, products and equipments for the manufacturing line. Even in this case, the size matters. The large size of CAD data makes it difficult for us to directly use CAD data for simulation. As the CAD data and simulation data differs in their own purpose, we can reduce the size of the CAD data without losing simulation purpose. In this paper we propose effective methods for reducing the size of the CAD data and re-using them for simulation, assuming the 3D CAD data are already available.

AN OPTIMIZATION PROCEDURE TO RECONSTRUCT THE AUTOMOBILE INGRESS MOVEMENT

Ait El Menceur M. O., P. Pudlo, F.-X. Lepoutre and P. Gorce

To simulate the automobile ingress movement, joint angles are needed. The joint angles are computed from the experimental data issued from an optoelectronic motion capture system. As these systems are often corrupted by problems linked either to the system or to the experimentation, the computed angles are biased. Lempereur et al., (2003b) proposed an optimization procedure to remedy to this problem. However, their method gives good results only on the end effectors trajectories, while the other bodies’ trajectories are not considered by their method. That degrades their positions and causes eventual collisions of these parts with the vehicle’s parts. On the other hand the corrected angles present some vibrations causing unrealistic simulation. In this paper we present a multi objective optimization based procedure to correct the joint articulation angles in automobile ingress movement for an elderly person. Our method minimises the distance between all reconstructed trajectories with the real ones at each step of time. Our method follows a kind of compromise between all trajectories of the model. Our method gives better global results. Correction of the joint angles allows a realistic simulation.

USING STEREO VISION AND TACTILE SENSOR FEATURES - For Grasp Planning Control

Madjid Boudaba, Nikolas Gorges, Heinz Woern and Alicia Casals

Planning the grasp positions either from vision or tactile sensor one can expected various uncertainties. This paper describes a matching schemes based on stereo vision and tactile sensor. To control the grasp planning execution, initially, the grasping positions are generated from stereo features, then the feedback of tactile features is used to match those positions. The result of matching algorithm is used to control the grasping positions. The grasping process proposed is experimented with an anthropomorphic robotic system.

FOOT STEP PLANNING FOR BIPED ROBOT BASED ON FUZZY Q-LEARNING APPROACH

Christophe Sabourin, Kurosh Madani, Weiwei Yu and Jie Yan

Biped robots have more flexible mechanical system and can move in more complex environment than wheeled robots. Its abilities to step over static or dynamic obstacles allow to the biped robot to cross uneven terrain where ordinary wheeled robots can fail. Consequently, the choice of the landing point for the foot of the swing leg is crucial when biped robots moves in uneven terrain. In this paper we present a footstep planning allowing to biped robots to step over dynamic obstacles. This can be done by adjusting step-length of the biped robot in advance. Our footstep planning strategy is based on a fuzzy Q-learning concept. In comparison with other previous works, one of the most interest of our approach is its good robustness because the proposed footstep planning is also efficient in the case of unpredictable motion of the obstacle.

ENVIRONMENT FOR DESIGNING AND SIMULATING CONTROL NETWORKS AT DIGITAL HOME

Jorge Azorín-López, Rafael J. Valdivieso-Sarabia, Andrés Fuster-Guill and Juan M. García-Chamizo

A design and simulation environment for control network is presented. Design of control networks could be complex task because there are many heterogeneous technologies. Each network technology uses its own design and configuration software. Also it is necessary realize network installation to validate the correct operation. This fact introduces high temporal and economical costs in the network installation. Simulation as a task inside design methodology allows detect errors prematurely since checks are made to a high level of abstraction. Our approach proposes a design and simulation environment of control network inside digital home. It is based on a design independent from any technology and leaves for latest tasks the technology election. It incorporates a simulation task that allows simulate the network behaviour designed at environment

PEOPLE TRACKING USING LASER RANGE SCANNERS AND VISION

Andreas Kräußling, Bernd Brüggemann, Dirk Schulz and Armin B. Cremers

Tracking multiple crossing people is a great challenge, since common algorithms tend to loose some of the persons or to interchange their identities when they get close to each other and split up again. In several consecutive papers it was possible to develop an algorithm using data from laser range scanners which is able to track an arbitrary number of crossing people without any loss of track. In this paper we address the problem of rediscovering the identities of the persons after a crossing. Therefore, a camera system is applied. An infrared camera detects the people in the observation area and then a charge--coupled device camera is used to extract the colour information about those people. For the representation of the colour information the HSV colour space is applied using a histogram. Before the crossing the system learns the mean and the standard deviation of the colour distribution of each person. After the crossing the system relocates the identities by comparing the actually measured colour distributions with the distributions, which have been learned before the crossing. Thereby, a Gaussian distribution of the colour values is assumed. The most probably assignment of the identities is then found using Munkres' Hungarian algorithm. It is proven with data from real world experiments that our approach can reassign the identities of the tracked persons stable after a crossing.

VISUAL BASIC APPLICATIONS FOR SHAPE MEMORY ELEMENTS DESIGN USED IN INTELLIGENT SYSTEMS

Sonia Degeratu, Petre Rotaru, Horia Octavian Manolea, Gheorghe Manolea, Anca Petrisor and Bizdoaca Nicu George

The paper presents the design strategies for two typical configurations of intelligent systems, using as active elements the Shape Memory Alloy (SMA) cantilever strip and the SMA helical spring. Based on the advantages and unique properties of SMA’s the authors defined the operating mode, the mechanical considerations, the design assumptions and the computation algorithms for these two examples. It also includes the experimental results of thermal analysis in order to determine the transformation temperatures for studied SMA elements. A comprehensive graphical interface, which runs under Visual Basic environment, has been developed for each design strategy. Each one provides a user friendly environment that allows intelligent system parameters configuration as well as the choice of the most adapted analysis methods and data displaying. At this moment, these two Visual Basic applications are used for engineering purposes as well as didactical ones.

COOPERATIVE LOCALIZATION - Self-configuring Procedure of a Multi-robot Localization System with Passive RFID Technology

Mikko Elomaa, Aarne Halme and François Vacherand

This preliminary simulation study introduces methods to configure a low cost localization system based on existing passive RFID technology. A group of small robots work together in order to configure the system autonomously. Bayesian probabilistic estimation methods are used for data fusion. The robots should be able to build and expand the localization system without human aid. When properly configured the system is able to offer positioning information with bounded error. The use of passive RFID tags as beacons makes the cost of expanding the robots' working area negligible.

FROM CAD MODEL TO HUMAN-SCALE MULTIMODAL INTERACTION WITH VIRTUAL MOCK-UP - An Automotive Application

Damien Chamaret, Paul Richard and Jean-Louis Ferrier

This paper presents and validates a new methodology for the efficient integration of CAD models in a physical-based virtual reality simulation. User interacts with virtual mock-up using a string-based haptic interface that may provides haptic sensation to both hands in a large workspace. Visual and tactile displays provide users with sensory feedback and improve both user performance and immersion. Stereoscopic images are displayed on a 2m x 2.5m retro-projected screen and viewed using polarized glasses. The proposed methodology implemented in a low-cost system, has been tested with an automotive application task. However, the presented approach is general enough to be applicable to a large variety of industrial applications.

PROSPECTIVE ROBOTIC TACTILE SENSORS - Elastomer-Carbon Nanostructure Composites as Prospective Materials for Flexible Robotic Tactile Sensors

Maris Knite, Gatis Podins, Sanita Zike, Juris Zavickis and Velta Tupureina

Our recent achievements in the design, processing and studies of physical properties of elastomer – nano-structured carbon composites as prospective compressive strain sensor materials for robotic tactile elements are presented. Polyisoprene matrix and high-structured carbon black filler as well as polyisoprene matrix and multi-wall carbon nanotube filler composites were designed and manufactured. Fully flexible conductive polymer nanocomposites for tactile sensing elements were developed. The electrical resistance of composites as the function of mechanical strain and pressure has been investigated.

TEMPORAL SMOOTHING PARTICLE FILTER FOR VISION BASED AUTONOMOUS MOBILE ROBOT LOCALIZATION

Walter Nisticò and Matthias Hebbel

Particle filters based on the Sampling Importance Resampling (SIR) algorithm have been extensively and successfully used in the field of mobile robot localization, especially in the recent extensions (Mixture Monte Carlo) which sample a percentage of particles directly from the sensor model. However, in the context of vision based localization for mobile robots, the Markov assumption on which these methods rely is frequently violated, due to ``ghost percepts'' and undetected collisions, and this can be troublesome especially when working with small particle sets, due to limited computational resources and real-time constraints. In this paper we present an extension of Monte Carlo localization which relaxes the Markov assumption by tracking and smoothing the changes of the particles' importance weights over time, and limits the speed at which the samples are redistributed after a single resampling step. We presents the results of experiments conducted on vision based localization in an indoor environment for a legged-robot, in comparison with state of the art approaches.

SLAM AND MULTI-FEATURE MAP BY FUSING 3D LASER AND CAMERA DATA

Ayman Zureiki, Michel Devy and Raja Chatila

Indoor structured environments contain an important number of planar surfaces and line segments. Using these both features in a unique map gives a simplified way to represent man-made environments. Extracting planes and lines by a mobile robot requires more than one sensor: a 3D laser scanner and a camera can be a good equipment. The incremental construction of such a model is a Simultaneous Localisation And Mapping (SLAM) problem: while exploring the environment, the robot executes motions; from each position, it acquires sensory data, extracts perceptual features, and simultaneously, performs self-localisation and model update. First, the 3D range image is segmented into a set of planar faces which are used as landmarks. Next, we describe how to extract 2D line landmarks by fusing data from both sensors. Our stochastic map is of heterogeneous type and contains plane and 2D line landmarks. At first, The SLAM formalism is used to build a stochastic planar map, and results on the incremental construction of such a map are presented, further on, heterogeneous map will be constructed.

CLOCK SYNCHRONIZATION IN INDUSTRIAL AUTOMATION NETWORKS - Comparison of Different Syntonization Methods

Dragan Obradovic, Ruxandra Lupas Scheiterer, Chongning Na, Günter Steindl and Franz-Josef Goetz

Synchronization of distributed clocks is a critical task in many real time applications over Ethernet. The Ethernet protocol, due to its non-deterministic nature, is not suitable for real-time applications with very strict synchronicity requirements. However, the limit is continuously being pushed outwards by current research. The Precision Time Protocol (PTP), delivered by the IEEE 1588 standard, provides high synchronization accuracy and has been adopted in many real time applications in the areas of industrial automation, measurement & control, communications etc. This paper will discuss several issues aimed at improving the synchronization performance.

STABLE STATES TRANSITION APPROACH - A New Strategy for Walking Robots Control in Uncertain Environments

Anca Petrişor, Nicu George Bîzdoacă, Adrian Drighiciu, Ilie Diaconu, Sonia Degeratu, Gabriela Canureci and Gabriela Petropol Serb

A new strategy for walking robots control in uncertain environments, called Stable States Transition Approach (SSTA), is proposed in this paper. All the controls, both the steps succession and the evolution inside each step are established by the evolution environment and by the objective proposed during the evolution. There are no predetermined types of legs movements; they are on-line determined during the robot evolution, irrespective of the ground shape. To apply this strategy it was necessary the robot interpretation as a Variable Causality Dynamic Systems (VCDS). Experimental results are implemented and verified in RoPa, a platform for simulation and design of walking robot control algorithms, to demonstrate the efficacy of the proposed control method

VISUAL TRACKING ON THE GROUND - A Comparative Analysis

Jorge Raul Gomez, Jose J. Guerrero and Elias Herrero-Jaraba

Tracking is an important field in visual surveillance systems. Trackers have been applied traditionally in the image, but a new concept of tracking has been used gradually, applying the tracking on the ground map of the surrounding area. The purpose of this article is to compare both alternatives and prove that this new usage makes possible to obtain a higher performance and a minimization of the projective effects. Moreover, it provides the concept of \emph{multi-camera} as a new tool for mobile object tracking in surveillance scenes, because a common reference system can be defined without increasing complexity. An automatic camera re-calibration procedure is also proposed, which avoids some practical limitations of the approach.

SHAPE MEMORY ALLOY TENDONS ACTUATED TENTACLE ROBOTIC STRUCTURE - Models and Control

Nicu George Bîzdoaca, Anca Petrisor, Elvira Bizdoaca, Ilie Diaconu and Sonia Degeratu

A tentacle manipulator is a manipulator with a great flexibility, with a distributed mass and torque that can take any arbitrary shape. Technologically, such systems can be obtained by using a cellular structure for each element of the arm. Shape memory alloy actuation offers an interesting solution, using the shape transformation of the wire/structure in the moment of applying a thermal type transformation able to offer the martensitic temperature. In order to assure an efficient control of SMA actuator applied to inverted pendulum, a mathematical model and numerical simulation of the resulting model is required. Due a particular possibility SMA actuator connection, a modified dynamics for wire or tendon actuation is presented. For an efficient study a Simulink block set is developed (block for user configurable shape memory alloy material, configurable block for dynamics of single link robotic structure, block for user configurable wire/tendon actuation). As conventional control possibilities were explored, the fuzzy control structure applied in this paper, offer an improved response. A more compact SMA actuation is proposed and experimented. The results are commented.

(A) VISION FOR 2050 - The Road Towards Image Understanding for a Human-Robot Soccer Match

Udo Frese and Tim Laue

We believe it is possible to create the visual subsystem needed for the RoboCup 2050 challenge – a soccer match between humans and robots – within the next decade. In this position paper, we argue, that the basic techniques are available, but the main challenge will be to achieve the necessary robustness. We propose to address this challenge through the use of probabilistically modeled context, so for instance a visually indistinct circle is accepted as the ball, if it fits well with the ball’s motion model and vice versa. Our vision is accompanied by a sequence of (partially already conducted) experiments for its verification. In these experiments, a human soccer player carries a helmet with a camera and an inertial sensor and the vision system has to extract all information from that data, a humanoid robot would need to take the human’s place.

THE ROLE OF SENSORY-MOTOR COORDINATION - Identifying Environmental Motion Dynamics with Dynamic Neural Networks

Stephen Paul McKibbin, Bala Amavasai, Arul N. Selvan, Fabio Caparrelli and W. A. F. W. Othman

We describe three recurrent neural architectures inspired by the proprioceptive system found in mammals; Exo-sensing, Ego-sensing, and Composite. Through the use of Particle Swarm Optimisation the robot controllers are adapted to perform the task of identifying motion dynamics within their environment. We highlight the effect of sensory-motor coordination on the performance in the task when applied to each of the three neural architectures.

DETECTING TRANSIENT WEATHER PHENOMENA ON MARS - An Overview of the Design and Calibration of Multiparametric Detection Algorithms for the REMS/MSL Mission

J. Verdasca, J.-A. Manfredi and V. Peinado

In its baseline operation mode the REMS/MSL mission is not well suited to characterize transient weather phenomena evolving on multiple scales. In this paper we argue that this limitation can be overcome by enabling REMS to autonomously detect sudden and unexpected changes in the acquired data and subsequently extend the time allocated for measurements. Detection is accomplished by means of multiparametric Event-Finding Algorithms running on the REMS micro-controller. We describe the principles underlying the design of such algorithms and the methods for their calibration.

MULTI-LEVEL CONTROL OF AN INTELLIGENT WHEELCHAIR IN A HOSPITAL ENVIRONMENT USING A CYBER-MOUSE SIMULATION SYSTEM

Rodrigo A. M. Braga, Marcelo Petry, Eugenio Oliveira and Luis Paulo Reis

The development of intelligent wheelchairs is a very good solution to assist severely handicapped people who are unable to operate classical electrical wheelchair by themselves in their daily activities. This paper describes the integration of a robotic simulator with our intelligent wheelchair shared control and planning modules. An adapted version of the free Cyber-Mouse robotic simulator was used to simulate the movement of the intelligent wheelchair in a hospital environment. Adaptations of the subsumption architecture, Strips Planning and A* Algorithms were employed and integrated to allow wheelchair intelligent behavior. The experimental results have demonstrated the success of the integration of these algorithms in our simulator allowing very safe motion of the intelligent wheelchair in the simulated hospital environment. Also, the adapted Cyber-Mouse simulator proved its capability and robustness in simulating the hospital environment and wheelchair physic characteristics.

PARAMETERIZATION AND INITIALIZATION OF BEARING-ONLY INFORMATION - A Discussion

R. Aragues and C. Sagues

In this paper we discuss feature parameterization and initialization for bearing-only data obtained from vision sensors. The interest of this work refers to the comparison of the bearing-only data representations and initialization techniques. The algorithm behavior is analyzed for different robot motions and depth of the features. The results are evaluated in terms of the sensitivity to step size and the performance to ill conditioned situations. The problem studied refers to robots moving on the plane, sensing the environment and extracting bearing-only information from uncalibrated camera to recover the position of the landmarks and its own localization.

BEHAVIOR BASED DEPENDABILITY ESTIMATION - Estimating the Dependability of Autonomous Mobile Systems using Predictive Filter

Jan Rüdiger, Achim Wagner and Essam Badreddin

Dependability is getting a more important non-functional property of a system. Measuring and predicting the dependability is especially important for autonomous or semi-autonomous and safety-critical systems. Since, at least for (semi-) autonomous systems, those systems are usually described by their behavior, a definition for dependability based on the behavior of the system is evident. In this paper the behavioral based definition of dependability was used together with a particle filter to estimate the dependability of an autonomous mobile system.

PREBUFFERING AS A WAY TO EXCEED THE DATA TRASFER SPEED LIMITS IN MOBILE CONTROL SYSTEMS

Ondrej Krejcar

The proliferation of mobile computing devices and local-area wireless networks has fostered a growing interest in location-aware systems and services. Additionally, the ability to let a mobile device determine its location in an indoor environment supports the creation of a new range of mobile control system applications. Main area of interest is in model of radio-frequency based system enhancement for locating and tracking users of our control system inside buildings. The developed framework described here joins the concepts of location and user tracking as an extension for new control system. The experimental framework prototype uses a WiFi network infrastructure to let a mobile device determine its indoor position. User location is used to data pre-buffering and pushing information from server to user’s PDA. All the server data are saved as artefacts with their position info in building.

MULTI-AGENT ARCHITECTURE FOR SIMULATION OF TRAFFIC WITH COMMUNICATIONS

Pedro Fernandes and Urbano Nunes

Inter-vehicle communications, in the context of Intelligent Transportation Systems, will probably bring a significant improvement in both traffic safety and efficiency. In order to evaluate in what measure this is true, traffic simulations that take into account the communications between vehicles are needed. Several ap-proaches are being pursued to this end, many of them working on the integration of existing traffic simula-tors and network simulators. However, this integration is, in most cases, done offline, not allowing real-time operation. Another line of research proposes traffic simulation with the use of agents, allowing the develop-ment of more adaptive systems. However, these proposals don't consider implicit vehicle communications and its integrated simulation. In this paper, we propose an agent-based architecture, in which the simulation and management of the inter-vehicle communications are integrated in simulated agent-based vehicles and infrastructure, in a hierarchical multi-agent environment. An overview of multi-agent methodologies, platforms, among other, is presented.

A WAIT-FREE REALTIME SYSTEM FOR OPTIMAL DISTRIBUTION OF VISION TASKS ON MULTICORE ARCHITECTURES

Thomas Müller, Pujan Ziaie and Alois Knoll

As multicore PCs begin to get the standard, it becomes increasingly important to utilize these resources. Thus we present a multithreaded realtime vision system, which distributes tasks to given resources on a single off-the-shelf multicore PC, applying an optimal-backoff scheduling strategy. Making use of an asynchronous data management mechanism, the system also shows non-blocking and wait-free behaviour, while data access itself is randomized, but weighted. Furthermore we introduce the top-down concept of {\em Interpretation-Based Preselection} in order to enhance data retrieval and a tracking based data storage optimization. On the performance side we prove, that functional decomposition and discrete data partitioning result in an almost linear speed-up due to excellent load balancing capability with concurrent function- and data-domain parallelization.

TORQUE CONTROL WITH RECURRENT NEURAL NETWORKS

Guillaume Jouffroy

In the robotics field, a lot of attention is given to the complexity of the mechanics and particularly to the number of degrees of freedom. The oscillatory recurrent neural network architecture is merely considered as a black box, which prevent from carefully studying the interesting dynamics of the network. In this paper we describe a generalized teacher forcing algorithm, and we build a default oscillatory recurrent network controller for a one degree of freedom vehicle. We then build a feedback system as a constraint method for the joint. We show that with the default oscillatory controller the vehicle can however behave correctly, even in its transient time from standing to moving, and is robust to the oscillatory controller's own transient period and its initial conditions. We finally discuss how the default oscillator can be permanently adapted with the help of the desired target which are produced by the controller in a mutual entrainment with the adaptive constraint feedback.

INTELLWHEELS - A Development Platform for Intelligent Wheelchairs for Disabled People

Rodrigo A. M. Braga, Marcelo Petry, Antonio Paulo Moreira and Luis Paulo Reis

Many people with disabilities find it difficult or even impossible to use traditional powered wheelchairs independently by manually controlling the devices. Intelligent wheelchairs are a very good solution to assist severely handicapped people who are unable to operate classical electrical wheelchair by themselves in their daily activities. This paper describes a development platform for intelligent wheelchairs called IntellWheels. The intelligent system developed may be added to commercial powered wheelchairs with minimal modifications in a very straightforward manner.. The paper describes the concept and the design of the platform and also the intelligent wheelchair prototype developed to validate the approach. Preliminary results concerning automatic movement of the IntellWheels prototype are also presented.

A KNOWLEDGE-BASED COMPONENT FOR HUMAN-ROBOT TEAMWORK

Pedro Santana, Luís Correia, Mário Salgueiro, Vasco Santos and José Barata

Teams composed of humans, software agents and robots pose a new challenge to the field of teamwork. This stemsfrom the fact that robots and humans have significantly different perceptual, reasoning, and acting capabilities. This paper contributes to this problem in a two folded way. First, it proposes a knowledge-based multi-agent system to support design and execution of stereotyped (i.e. recurring) human-robot teamwork. Secondly, it proposes a workflow based model for both loosely and tightly coupled human-robot interactions, in addition to its implementation. Rather than focusing on automatic teamwork (re)planning, this paper proposes a complementary and intuitive knowledge-based solution for fast deployment and adaptation of small scale teams operating in life threatning tasks. A team for humanitarian demining composed of two humans and one robot performing a scan with a scent sensor has been selected as demonstrating case study.

OBJECT EXPLORATION WITH A HUMANOID ROBOT - Using Tactile and Kinesthetic Feedback

Nicolas Gorges, Stefan Gaa and Heinz Wörn

This work deals with the reactive exploration of objects with a humanoid robot using only tactile and kinesthetic sensor feedback. To coordinate the flow of the exploration, a hierarchical system is introduced. The lowest level extracts contacts points and elementary features based on the direct contact with the object. It also provides elementary movement primitives. The intermediate level consists of different controlling behaviors in order to generate exploration movements based on the resulting sensor feedback. This level enables the robot to track an object pointwisely or continously. The highest level evaluates the process of the exploration and determinates the reactive behavior of the underlying components. The evaluation scenario comprises the exploration of edges, which are arbitrarily located in space. The evaluation platform consists of a robot arm, a force-torque sensor, and a tactile sensor matrix. The proposed approach is evaluated and the different reactive behaviors as well as the used sensor modalities are compared.

LICENSE PLATE NUMBER RECOGNITION - New Heuristics and a Comparative Study of Classifiers

César García-Osorio, José-Francisco Díez-Pastor, Juan J. Rodríguez and Jesús Maudes

We describe an artificial vision system used to recognize the Spanish car license plate numbers in raster images. The algorithm is designed to be independent of the distance of the car to the camera, the size of the plate number, the inclination and the light conditions. In the preprocessing steps the algorithm takes a raster image as input, and gives an ordered list of license plate areas candidates. Only in very rare occasions the second and third candidates are needed, most of the cases the first candidate is the correct one. During the preprocessing a new filter has been used. This filter it is only applied to those areas of the image with low values of saturation, achieving this way better results. In order to choose the best classifier for the classifying stage, a comparative study has been performed using the data mining tool Weka.

EFFICIENT PLANNING OF AUTONOMOUS ROBOTS USING HIERARCHICAL DECOMPOSITION

Matthias Rungger, Olaf Stursberg, Bernd Spanfelner, Christian Leuxner and Wassiou Sitou

This paper considers autonomous robots which are expected to act in highly dynamic environments. This implies for model-based planning that world models are of relatively high complexity to capture all relevant aspects and dependencies of the environment. Most existing planning algorithms are not able to efficiently generate plans for the resulting model complexity. To allow robots to make immediate and reliable decisions, adequate reduction of complexity is needed. This paper proposes a layered architecture to apply abstraction and separation of concerns as suitable measures to partition the problem space. We describe the hierarchical layers in terms of formal models and present first results of the application of the architecture.

REMOTE ROBOT CONTROL AND HIGH AVAILABILITY

Silvia Anton, Florin Daniel Anton and Theodor Borangiu

Nowadays production flows are modular, each module in the enterprise being specialized and used to achieve a particular task. In many cases the modules are connected and materials are sequentially processed in each module resulting a final, unique product or assembly. One typical such production module is a flexible cell/system using multiple robots. In this structure, providing continuous service for applications is a key component of a successful robotized implementing of manufacturing. High availability (HA) is one of the components contributing to continuous service provision for applications, by masking or eliminating both planned and unplanned systems and application downtime. A high availability solution will ensure that the failure of any component of the solution - either hardware, software or system management, will not cause the application and its data to become permanently unavailable. A high availability solution in robotized manufacturing provides automated failure detection, diagnosis, application recovery, and node (robot controller) re integration. The paper describes a platform which is a software product designed to control and supervise multiple robot-vision controllers using remote connections with a number of Adept Technology V+ controllers configured to use a high availability implementation, either located in a local network or via Internet.

DESIGN AND BALANCING CONTROL OF AIT LEG EXOSKELETON-I (ALEX-I)

Narong Aphiratsakun, Kittipat Chirungsarpsook and Manukid Parnichkun

This paper is focused on the design of mechanical hardware, controller architectures, and analysis of balancing control at the Asian Institute of Technology Leg EXoskeleton-I (ALEX-I). ALEX-I has 12 DOF (6 DOF for each leg: 3 at the Hip, 1 at the knee and 2 at the ankle), controlled by 12 DC motors. The main objective of the research is to assist patients who suffer from the paraplegia and immobility due to the loss of lower limbs. ALEX-I’s parts and assembly are designed on CAD software, SolidWorks, exported to MATLAB simulation environment, and observed using 3D VRML script interpreter to investigate balancing postures of the exoskeleton. The simulation model is proven to be accurate by comparing the resulting kinematics characteristics with the results from Corke’s MATLAB This paper is focused on the design of mechanical hardware, controller architectures, and analysis of balancing control at the Asian Institute of Technology Leg EXoskeleton-I (ALEX-I). ALEX-I has 12 DOF (6 DOF for each leg: 3 at the Hip, 1 at the knee and 2 at the ankle), controlled by 12 DC motors. The main objective of the research is to assist patients who suffer from the paraplegia and immobility due to the loss of lower limbs. ALEX-I’s parts and assembly are designed on CAD software, SolidWorks, exported to MATLAB simulation environment, and observed using 3D VRML script interpreter to investigate balancing postures of the exoskeleton. The simulation model is proven to be accurate by comparing the resulting kinematics characteristics with the results from Corke’s MATLAB Robotics Toolbox (Corke, 1996). PC104 is employed as the main (master) processing unit for calculation of the balanced gait motion corresponding to feedback signals from the force sensors mounted at the two feet plates, whereas ARM7’s are used for the low-level (slave) control of the angular position of all joints. The balanced posture set-points (joint trajectories) under the Center of Mass (CM) Criterion are generated in the simulation before testing on the real mechanical parts is implemented to avoid damaging the system.

HOW TO ASSESS RELIABILITY OF INDUSTRIAL WIRELESS SOLUTIONS

Lutz Rauchhaupt and Marko Krätzig

Wireless communication is an emerging technology for industrial automation applications. Many solutions are available which more or less consider industrial related requirements. One of the main concerns of industrial automation system users is the reliability of wireless communication. The subject of this paper is a method to assess reliability of wireless communication from the point of view of industrial automation applications. Characteristic parameters are introduced which can be used in analytical studies, in network simulations or measurements to assess reliability with respect to intended industrial control processes. In particular the different use cases for the characteristic parameters are pointed out as well as the stochastic nature of these parameters. Finally the influences are mentioned which have to be taken into account while assessing wireless industrial communication systems.

FLEXIBLE TRAJECTORY GENERATION TO EXTEND HUMAN-ROBOT INTERACTION WITH DYNAMIC ENVIRONMENT ADAPTATION

Xavier Giralt and Josep Amat

In our daily life, we use many elements that help us by means of a higher protection level (thimble, door stop) or by improving our dexterity (funnel, compasses). Both kinds of elements allow us to execute well known tasks with less concentration, faster, and, above all, improving performance. Like the real tools mentioned above, in the robotics field, virtual constraints enhance human-machine interaction. This work presents a multi-parametric behaviour model for an agent that increases task safety, and enables higher integration possibilities. The model presented here allows the perturbation of a programmed task, by introducing virtual elastic and viscous forces. This work presents the behaviour model, a description of its implementation and experimental results in human-robot interaction.

USING THE OAG TO BUILD A MODEL DEDICATED TO MODE HANDLING OF FMS

Nadia Hamani, Nathalie Dangoumau and Etienne Craye

This paper deals with a modeling approach for reactive mode handling of Flexible Manufacturing Systems (FMS). We show that using the plant model enables to establish aggregate operations. These are generic entities which depend only on the plant and do not depend on production goals. Aggregate operations are then used for building the model dedicated to mode handling. This study is illustrated through an example of a flexible manufacturing cell.

REPRESENTATION OF ODOMETRY ERRORS ON OCCUPANCY GRIDS

Anderson A. S. Souza, Andre M. Santana, Ricardo S. Britto, Luiz M. G. Gonçalves and Aderlardo A. D. Medeiros

In this work we propose an enhanced model for mapping from sonar sensors and odometry that allows a robot to represent an environment map in a more suitable way to both the sonar sensory data and odometry system of the robot. We use a stochastic modelling of the errors that brings up reliable information. As a contribution, we obtain a final map that is more coherent with the reality of the original data provided by the robotic system. Practical experiments show the results obtained with the proposed modification to be trustable in such a way that this map can be used to provide previous knowledge to the mobile robot in order to perform its tasks in an easier and accurate way. Moreover, the map can help the robot to support unexpected situations inside of the environment.

DYNAMIC-BASED SIMULATION FOR HUMANOID ROBOT WALKING USING WALKING SUPPORT SYSTEM

Aiman Musa M. Omer, Yu Ogura, Hideki Kondo, Hun-ok Lim and Atsuo Takanishi

A new humanoid bipedal robot WABIAN-2R was developed to simulate human motion. WABAIN-2R is able to perform similar human-like walking motion. Moreover, the robot is able to perform walking motions with a passive walk-assist machine. However, walking with an active walk-assist machine is expected to be unstable. Conducting this experiment is highly risky and costly. Therefore, we had developed a dynamic simulator in order to test walking robot with walk-assist machine before conducting it in real simulation.

COMPARISON OF DIFFERENT INFORMATION FLOW ARCHITECTURES IN AUTOMATED DATA COLLECTION SYSTEMS

Jussi Nummela, Petri Oksa, Leena Ukkonen, Lauri Sydänheimo and Markku Kivikoski

Automated Data Collecting System (ADCS) is a common name for automatic systems that collect data of any kind. These systems are becoming more and more common in several industries and play an important part in many of today’s and future applications. Information flow architecture is an important issue, when employing an ADCS. This paper presents different kinds of architecture models and their typical characteristics, concentrating on traffic load issues in different parts of the system. The results presented in this paper, give a basis for more accurate specifying and designing of the architecture model for each automated data collecting application in question.

LOCALIZATION OF A MOBILE ROBOT BASED IN ODOMETRY AND NATURAL LANDMARKS USING EXTENDED KALMAN FILTER

Andre M. Santana, Anderson A. S. Sousa, Ricardo S. Britto, Pablo J. Alsina and Adelardo A. D. Medeiros

This work proposes a localization system for mobile robots using the Extended Kalman Filter. The robot navigates in an known environment where the lines of the floor are used as natural landmarks and identifiquedby using the Hough transform.The prediction phase of the Kalman Filter is implemented using the odometrymodel of the robot. The update phase directly uses the parameters of the lines detected by the Hough algorithm to correct the robot’s pose.

A DISTRIBUTED HARDWARE-SOFTWARE ARCHITECTURE FOR CONTROL AN AUTONOMOUS MOBILE ROBOT

Ricardo S. Britto, Andre M. Santana, Anderson A. S. Souza, Adelardo A. D. Medeiros and Pablo J. Alsina

In this paper, we introduce a hardware-software architecture for controlling the autonomous mobile robot Kapeck. The Kapeck robot is composed of a set of sensors and actuators organized in a CAN bus. Two embedded computers and eigth microcontroller-based boards are used in the system. One of the computers hosts the vision system, due to the significant processing needs of this kind of system. The other computer is used to coordinate and access the CAN bus and to accomplish the other activities of the robot. The microcontroller-based boards are used with the sensors and actuators. The robot has this distributed configuration in order to exhibit a good real-time behavior, where the response time and the temporal predictability of the system is important. We adopted the hybrid deliberative-reactive paradigm in the proposed architecture to conciliate the reactive behavior of the sensors-actuators net and the deliberative activities required to accomplish more complex tasks.

POSITION CONTROL METHOD OF A NON-CONTACTING CONVEYANCE SYSTEM FOR STEEL STRIP

Yeongseob Kueon, Hyoung Jin Yoon and Yoon Su Baek

Electromagnetic application system to improve the surface quality of steel strip is getting popular because customers demand better surface quality of steel strip. To realize such a requirement, non-contact conveyance methods by means of air floater and electromagnetic levitation and propulsion were considered. However, air floating method is not easy to control of the position of steel strip since the system is highly nonlinear. And thus, the application of a magnetic levitation and propulsion to steel strip conveyance is suitable. Sensors measuring positions of steel strip also need to be non-contact in order to maintain non-contact and simple characteristics of the system. This paper proposes the method of the spatial position estimation of steel plate without using sensors. This method simplifies non-contact conveyance system and cuts down expenses of the system. Spatial positions of steel strip can be estimated by currents supplied for electromagnet to maintain a fixed air gap. Estimated positions are then fed back into the control system to do position control. Computer simulation and experimental results are provided to verify the suitability of the proposed system performance and concept.

CALCULATING SOFTWARE METRICS FOR LADDER LOGIC

Matthew Waters, Ken Young and Ira Baxter

Ladder logic is a graphical language widely used to program Programmable Logic Controllers (PLCs). PLCs are found at the heart of most industrial control systems used in automation because they are robust, they are relatively easy to program and because they are a proven technology. However there is currently no means to measure the intrinsic properties and qualities of the code produced. This paper details a method for creating tools to calculate software metrics for ladder logic, specifically Rockwell Automation’s implementation of ladder logic for its ControlLogix family of PLCs, Import-Export language version 2.6. Results obtained from these tools are briefly discussed also.

DETECTION AND CONTROL OF NON-LINEAR BEHAVIOR BY SLIDING MODES CONTROL IN A 3 D.O.F. ROBOT

Claudio Urrea and Marcela Jamett

Results from simulations of a Planar Robot Model, when it is placed in the same plane of the action of the gravity force are reviewed in this paper. The model includes several parameters usually discarded in current models, such as Driving, and Non-linear Friction, for an industrial-type robotic manipulator and its actuators. When we develop more exact representations of the dynamics of a manipulator and their actuators, chaotic behavior is detected for certain parameter values of the robotic manipulator. This chaotic behavior – without external inputs – was exactly controlled by Sliding Modes.

DESIGN OF AN ANALOG-DIGITAL PI CONTROLLER WITH GAIN SCHEDULING FOR LASER TRACKER SYSTEMS

Christian Wachten, Lars Friedrich, Claas Müller, Holger Reinecke and Christoph Ament

Laser trackers are important devices in position metrology. A moving reflector is tracked by a laser beam to determine its position in space. To ensure a proper function of the device the feedback control loop is an essential part. An analog PI controller with online parameter adaptation and absolute distance measurement ability is used to guarantee an optimal dynamic system. The feedback controller is connected to a quadrant detector which serves as the sensor element in the control loop. The position of an incoming laser beam is measured be the quadrant detector and the controller provides the input signals for a subsequent actuator. The control variable is the deviation of the laser beam from the centre of the diode which should ideally be zero. The actuator consists of two axes and each one is equipped with a rotatable mirror. The task of the controller is to rotate the mirrors in such a way so that the laser beam follows the movements of the reflector. To design an optimal controller linear, time-invariant models of the actuator and the position sensor are developed to optimize its parameters. The gain of the plant correlates with the distance between the reflector and the laser tracker. To achieve the optimal dynamic performance the controller is automatically adapted to the distance during operation. A method based on oscillation injection to measure the absolute distance is developed. Due to higher dynamic demands a standard analog PI controller is implemented with the controller gain tuned by digital potentiometers. A microcontroller is used to adjust the parameters and to estimate the distance. During the power up sequence and in case of a beam loss the system is completely controlled by the digital part.

OFF-LINE ROBUSTIFICATION OF PREDICTIVE CONTROL FOR UNCERTAIN SYSTEMS - A Sub-optimal Tractable Solution

Cristina Stoica, Pedro Rodríguez-Ayerbe and Didier Dumur

An off-line technique enabling to robustify an initial Model Predictive Control (MPC) for multivariable systems via the convex optimization of a Youla parameter is presented. Firstly, a multivariable predictive controller is designed for a nominal system and then robustified towards unstructured uncertainties. Secondly, we want that the controlled system remains stable in the presence of uncertainties acting in a polytopic domain around the nominal system. This condition leads to verify a Bilinear Matrix Inequality (BMI) for each vertex of the polytopic domain. This BMI can be mathematically relaxed to semi-definite programming (SDP) using a Sum of Squares (SOS) strategy, with a significant increase of the number of scalar decision variables. An alternative tractable solution for the BMI is proposed, which is based on the minimization of the complementary sensitivity function. In order to illustrate the potential of the developed method, an application to a simplified model of a stirred tank reactor is further proposed.

DISTURBANCES ESTIMATION FOR MOLD LEVEL CONTROL IN THE CONTINUOUS CASTING PROCESS

Karim Jabri, Bertrand Bele, Alain Mouchette, Emmanuel Godoy and Didier Dimur

This paper addresses the problem of mold level fluctuations in the continuous casting process, which strongly penalize the quality of the final product and lead to a costly machine downtime. Therefore, the mold level is controlled using a stopper as the flow control actuator and a level sensor. Under normal casting conditions, the current controllers provide suitable performances but abnormal conditions require manual intervention, such as the decrease of the casting speed, in particular when undesired disturbances like clogging/unclogging or bulging occur. These disturbances rise in severity for certain steel grades or at high casting speeds. Therefore, this paper focuses on the on-line disturbances estimation in order to introduce compensation actions. Starting with the presentation of the continuous casting process, the description of the model of the machine, and highlighting the main control challenges, an observer estimating clogging and bulging disturbances is then developed. This design may help future control architectures based on disturbances estimation. The proposed observer is finally validated by extracting disturbances from experimental signals measured on a continuous casting plant.

A RECURSIVE FRISCH SCHEME ALGORITHM FOR COLOURED OUTPUT NOISE

J. G. Linden and K. J. Burnham

A recursive (adaptive) algorithm for the identification of dynamical linear errors-in-variables systems in the case of coloured output noise is developed. The input measurement noise variance as well as the auto-covariance elements of the coloured output noise sequence are determined via two separate Newton algorithms. The model parameter estimates are obtained by a recursive bias-compensating instrumental variables algorithm with past noisy inputs as instruments, thus allowing the compensation for the explicitly computed bias at each discrete-time instance. The performance of the developed algorithm is demonstrated via simulation.

FREQUENCY CONTROL FOR ULTRASONIC PIEZOELECTRIC TRANSDUCERS, BASED ON THE MOVEMENT CURRENT

Constantin Voloşencu

This paper provides a method for frequency control at the ultrasonic high power piezoelectric transducers, using a feedback control systems based on the first derivative of the movement current. This method assures a higher efficiency of the energy conversion and greater frequency stability. A simulation for two kinds of transducer model is made. The method is implanted on a power electronic generator. Some transient characteristics are presented.

SYNTHESIS OF THE LOW-PASS AND HIGH-PASS WAVE DIGITAL FILTERS

B. Psenicka, F. Garcia-Ugalde and A. Romero Mier y Teran

In this paper we propose a very simple procedure for design and analysis of lowpass and highpass wave digital filters derived from reference filter given in the laticce configuration. Wave Digital Filter WDF derived from reference filter in lattice configuration can be designed with excellent pass band properties. They can be proposed and implemented without knowledge of classical filter theory. In this paper we present tables for Butterworth, Chebychev and Elliptic lowpass filter design.In the end of our article we realize WDF using Embedded Target for Texas Instruments TMS320C6000 DSP platform. The model of the WDF was created by means of serial and parallel blocks that were added to the window Simuling Library Browser between Comonly Used Blocks.

QOS MULTICAST ROUTING DESIGN USING NEURAL NETWORK

Ming Huang and Shang Ming Zhu

In this paper, an algorithm based on Hopfield neural network for solving the problem of determining minimum cost paths to multiple destination nodes satisfying QoS requirements is proposed. The schema of constructing the multicast tree with HNN is emphasized after the analysis of the attributes of the multicast tree. At last, the emulation explores the feasibility of this algorithm.

A HIGHER-ORDER STATISTICS-BASED VIRTUAL INSTRUMENT FOR TERMITE ACTIVITY TARGETING

Juan José González de la Rosa, José Melgar Camarero, Stephane Bouaud, J. G. Ramiro and Antonio Moreno Muñoz

In this paper we present the operation results of a portable computer-based measurement equipment conceived to perform non-destructive testing of suspicious termite infestations. Its signal processing module is based in the spectral kurtosis (SK), with the de-noising complement of the discrete wavelet transform (DWT). The SK pattern allows the targeting of alarms and activity signals. The DWT complements the SK, by keeping the successive approximations of the termite emissions, supposed more non-gaussian (less noisy) and with less entropy than the detail approximations. For a given mother wavelet, the maximum acceptable level, in the wavelet decomposition tree, which preserves the insects' emissions features, depends on the comparative evolution of the approximations details' entropies, and the value of the global spectral kurtosis associated to the approximation of the separated signals. The paper explains the detection criterion by showing different types of real-life recordings (alarms, activity, and background).

ON THE SAMPLING PERIOD IN STANDARD AND FUZZY CONTROL ALGORITHMS FOR SERVODRIVES - A Multicriterial Design and a Timing Strategy for Constant Sampling

Dan Mihai

The paper deals with the best choice for the control sampling period in term of a multicriterial conditioning, with the on-line timing and with a comparison between the conventional (like PI) control algorithms and the fuzzy control. Several useful relations are followed by diagrams obtained in simulation and by different real-time recordings both for the timing and for characteristic variables of the system. Implementations with microcontroller and DSP are used for analyzing the design criterion and the timing strategy. The application field concerns a servodrive, so the real-time constraints are quite strong. The author conceived a general control strategy for the on-line timing based on imbricate interrupts, each pulse encoder acting on the hardware input interrupt of the control processor.

ON THE SAMPLING PERIOD IN FUZZY CONTROL ALGORITHMS FOR SERVODRIVES - A Strategy for Variable Sampling

Dan Mihai

The paper deals with a variable control sampling period for the fuzzy control algorithms implemented on low inertia servodrives. The robustness of the fuzzy control strategy is extended on the sampling period values and hence an adaptive sampling algorithm is proposed. The author analyzes the possibility to vary continuously the sampling frequency upon a basic process variable. Principles, models and simulation results inserted here give reliance in this technique and an enhancement of the fuzzy control implementation. The distribution of the sampling moments in different adaptive conditions and the behaviour of the servodrive are obtained by means of some models and simulations in accordance with the real-time target hardware system.

RECURSIVE AND BACKWARD REASONING IN THE VERIFICATION ON HYBRID SYSTEMS

Stefan Ratschan and Zhikun She

In this paper we introduce two improvements to the method of verification of hybrid systems by constraint propagation based abstraction refinement that we introduced earlier. The first improvement improves the recursive propagation of reachability information over the regions constituting the abstraction, and the second improvement reasons backward from the set of unsafe states, instead of reasoning forward from the set of initial states. Detailed computational experiments document the usefulness of these improvements.

CONTROL THEORETIC APPROACH TO ANALYSIS OF RANDOM BRANCHING WALK MODELS ARISING IN MOLECULAR BIOLOGY

Andrzej Swierniak

We present three models of molecular processes described by infinite systems of first order differential equations. These models result from branching random walk processes used to represent the evolution of particles in these problems. Using asymptotic techniques based on Laplace transforms it is possible to characterize the asymptotic behavior of telomeres shortening which is supposed to be the mechanism of aging and death and cancer cells with increasing number of copies genes responsible for coding proteins causing drug removal or metabolisation. The analysis in both cases is possible because the models could be represented by systems with positive feedbacks. The third process analyzed is related to evolution of microsatellite repeats. The model is similar to the one for gene amplification evolution but in this case the positive feedback is not present. Analysis of stability for both these models in the case of infinitely many nonzero initial conditions is based on spectral analysis in Banach spaces.

SLIDING MODE CONTROL - Is it Necessary Sliding Motion?

L. Acho

Sliding mode control has been recognized to be insensitive to exogenous perturbations if the reachability conditions is warranted. Two phases follow the dynamics of the closed-loop perturbed system: 1) Finite-time convergence to the sliding surface, and 2) Sliding motion along the sliding surface. In the sliding motion the system has a reduced-order dynamic behavior. But, is it really necessary to have sliding motion to warranty the robustness property of the sliding mode controller? The main objective of this position paper is to theorize this important question.

FAULT DETECTION BY MEANS OF DCS ALGORITHM COMBINED WITH FILTERS BANK - Application to the Tennessee Eastman Challenge Process

Oussama Mustapha, Mohamad Khalil, Ghaleb Hoblos, Houcine Chafouk and Dimitri Lefebvre

Early fault detection, which reduces the possibility of catastrophic damage, is possible by detecting the change of characteristic features of the signals. The aim of this article is to detect faults in complex industrial systems, like the Tennessee Eastman Challenge Process, through on-line monitoring. The faults that are concerned correspond to a change in frequency components of the signal. The proposed approach combines the filters bank technique, for extracting frequency and energy characteristic features, and the Dynamic Cumulative Sum method (DCS), which is a recursive calculation of the logarithm of the likelihood ratio between two local segments. The method is applied to detect the perturbations that disturb the Tennessee Eastman Challenge Process and may lead the process to shut down.

A DYNAMIC MODEL OF A BUOYANCY SYSTEM IN A WAVE ENERGY POWER PLANT

Tom S. Pedersen and Kirsten M. Nielsen

A nonlinear dynamic model of the buoyancy system in a wave energy power plant is presented. The plant (“Wave Dragon”) is a floating device using the potential energy in overtopping waves to produce power. A water reservoir is placed on top of the WD, and hydro turbines lead the water to the sea producing electrical power. Through air chambers it is possible to control the level, the trim and the heel of the WD. It is important to control the level (and trim, heel) of the WD in order to maximize the power production in proportion to the wave height, here the amount of overtopping water and the amount of potential energy is conflicting. Five separate air chambers, all open to the sea, makes the device float. The pressures in the air chambers may be individually controlled by an air fan through an array of valves. In order to make a model-based control system, this paper presents a model describing the dynamics from the air inlet to the level, trim and heel. The model is derived from first principles and is characterized by physical parameters. Results from validation of the model against plant data are presented.

PATH PLANNING USING DISCRETIZED EQUILIBRIUM PATHS - A Robotics Example

Cornel Sultan

A methodology which uses equilibrium paths for the control of nonlinear systems is investigated. Sufficient conditions for the state space trajectory of the system to be arbitrarily close to an equilibrium path and for the evolution of the system to be quasistationary are determined using constructive proofs which result in piecewise constant controls. Examples from the field of robot path planning are used to illustrate the theoretical results.

NEAR OPTIMUM CONTROL OF A FULL CAR ACTIVE SUSPENSION SYSTEM

Paolo Lino and Bruno Maione

In this paper, a near-optimum control strategy applied to a full car model equipped with an active suspension system is presented. The control law is based on a reduced order model obtained by means of a modal aggregation method, achieving a compromise between computational effort in deriving the control law and system performances. To assess the controller performances, a virtual prototype of the suspension system is developed by using AMESim, an advanced fluid-mechanic developing tool. The virtual prototype could be assumed as a reliable model of the real system enabling to perform safer and cheaper tests than using the real system. Simulation results show the effectiveness of the approach.

A NEW APPROACH FOR MODELING ENVIRONMENTAL CONDITIONS USING SENSOR NETWORKS

Mehrdad Babazadeh and Walter Lang

An approach to estimate environmental conditions (EC), temperature, relative humidity and air flow in the specific wireless sensor node, slept for reducing battery-consumption or inactive due to either empty batteries or out-of-range, using surrounding active sensor nodes is presented. A combinational nonlinear multivariable model consists of interconnections is extracted and then using benefits of the sensor network it is broken to the linear dynamic model so that the unknown parameters could be verified by a simple identification process. The model developed is used to prediction for possible use in different applications such as designing model base controllers to adjusting EC in the specific nodes of closed space air conditioned systems as well as an estimator in fault diagnosis and energy management methods. Furthermore, the proposed approach is independent of the type of ventilation system.

HETEROGENEOUS IMAGE RETRIEVAL SYSTEM BASED ON FEATURES EXTRACTION AND SVM CLASSIFIER

Rostom Kachouri, Khalifa Djemal, Hichem Maaref, Dorra Sellami Masmoudi and Nabil Derbel

Image databases represent increasingly important volume of information, so it is judicious to develop powerful systems to handle the images, index them, classify them to reach them quickly in these large image databases. In this paper, we propose an heterogeneous image retrieval system based on feature extraction and Support vector machines (SVM) classifier. For an heterogeneous image database, first of all we extract several feature kinds such as color descriptor, shape descriptor, and texture descriptor. Afterwards we improve the description of these features, by some original methods. Finally we apply an SVM classifier to classify the consequent index database. For evaluation purposes, using precision/recall curves on an heterogeneous image database, we looked for a comparison of the proposed image retrieval system with an other Content-based image retrieval (CBIR) which is QUadtree-based Index for image retrieval and Pattern search (QUIP-tree). The obtained results show that the proposed system provides good accuracy recognition, and it prove more better than QUIP-tree method.

A FRAMEWORK FOR DISTRIBUTED AND INTELLIGENT PROCESS CONTROL

Qurban A. Memon

The customized design, development and implementation aspects of the Distributed Control System for process control in an environment of intelligent and tagged field devices; and Programmable Logic Controllers is the main focus of this work. The objectives include reduced operational requirements at central controller together with intelligent local processes to improve timely decision making at local level. The proposed solution consists of two-layer approach: use of decentralized intelligent agents at the local process level, and four-tier modular architecture at central controller level to help implement distributed intelligence at the local level. The design, development and configuration issues for such a customized design of DCS are investigated.

ROTATION-INVARIANT IRIS RECOGNITION - Boosting 1D Spatial-Domain Signatures to 2D

Stefan Matschitsch, Herbert Stögner, Martin Tschinder and Andreas Uhl

An iris recognition algorithm based on 1D spatial domain signatures is improved by extending template data from mean vectors to 2D histogram information. EER and shape of the FAR curve is clearly improved as compared to the original algorithm, while rotation invariance and the low computational demand is maintained. The employment of the proposed scheme remains limited to the similarity ranking scenario due to its overall FAR/FRR behaviour.

IDENTIFICATION OF MULTI-DIMENSIONAL SYSTEM BASED ON A NOVEL CRITERION

Yue Zhao, Kueiming Lo and Wook-Hyun Kwon

Most system recursive identification algorithms are based on the prediction error (PE) criterion. Such a recursive algorithm only considers the present estimation residual error instead of all estimation residuals. It would result in large estimation error when the signal noise disturbs strongly. In this paper, a new identification criterion is concerned for ARMAX systems disturbed by color noise. This cost function considers both the errors between the actual outputs and the estimation result and the difference of each estimation error. Under this performance function, based on the complexity of signals, a new recursive algorithm MSDCN (Multi-diemnsional System Disturbed by Color Noise) is proposed. This new recursive algorithm contains not only the present estimation residual error, but also the past estimation errors. It could reduce the influence of noise in multi-system identification, further decrease the prediction error. Several simulation examples are given to illustrate the method's anti-disturbance performance.

ASYMPTOTIC THEORY OF THE REACHABLE SETS TO LINEAR PERIODIC IMPULSIVE CONTROL SYSTEMS

E. V. Goncharova and A. I. Ovseevich

We study linear periodic control systems with a bounded total impulse of control. The main result is an asymptotic formula for the reachable set, which, at the same time, reveals the structure of the attractor --- the set of all limit shapes of the reachable sets. The attractor is shown to be parameterized by a (finite-dimensional) toric fibre bundle over a circle. The fibre of the bundle can be described via the Floquet multipliers (monodromy matrix) of the linear system. Moreover, the limit dynamics of shapes of reachable sets can be parametrized by an explicit curve on the toric bundle.

PASSIVITY OF A CLASS OF HOPFIELD NETWORKS - Application to Chaos Control

Adrian–Mihail Stoica and Isaac Yaesh

The paper presents passivity conditions for a class of stochastic Hopfield neural networks with state--dependent noise and with Markovian jumps. The contributions are mainly based on the stability analysis of the considered class of stochastic neural networks using infinitesimal generators of appropriate stochastic Lyapunov--type functions. The derived passivity conditions are expressed in terms of the solutions of some specific systems of linear matrix inequalities. The theoretical results are illustrated by a simplified adaptive control problem for a dynamic system with chaotic behavior.

RECURSIVE BIAS-COMPENSATING ALGORITHM FOR THE IDENTIFICATION OF DYNAMICAL BILINEAR SYSTEMS IN THE ERRORS-IN-VARIABLES FRAMEWORK

T. Larkowski, J. G. Linden, B. Vinsonneau and K. J. Burnham

The paper investigates a recursive approach for the bias compensating least squares (BCLS) technique. The method presented is applied to the problem of on-line identification of single-input single-output bilinear models in the errors-in-variables framework. Within this framework the recursive bilinear BCLS algorithm is realized when a bilinear Frisch scheme (BFS) is iteratively applied for the estimation of the parameters of an exemplary bilinear system, giving rise to the exact recursive BFS (ERBFS) method. Moreover, a further extension of the ERBFS incorporating Tikhonov regularization with variable exponential weighting is considered and this is shown to be beneficial in the initial period of the identification procedure.

A PROTOTYPE FOR ON-LINE MONITORING AND CONTROL OF ENERGY PERFORMANCE FOR RENEWABLE ENERGY BUILDINGS

Benjamin Paris, Julien Eynard, Gregory François, Thierry Talbert and Monique Polit

In this article, ways for improving the energetic performance of buildings are investigated. A state of the art leads to the introduction of a performance indicator expressed in kWh/m^2/yr. To improve the value of this indicator, a processor-based prototype of a real-time data-acquisition and monitoring system is developed in collaboration with two industrial companies. The set of measurements and corresponding sensors that are necessary to compute the value of the indicator while being consistent with the natural segmentation of energy consumption, is listed, thanks to the representation of the building using a systemic approach. Two control algorithms are tested in simulation to improve renewable energy consumption while reducing fossil energy dependence, which are deemed to be applicable in practice using the proposed electronics. Simulations concerning the control and optimization of the power applied to two warmers in a room show large potential for fossil energy consumption reduction.

REAL-TIME SYSTEMS SAFETY CONTROL CONSIDERING HUMAN MACHINE INTERFACE

José Machado and Eurico Seabra

In this paper it is presented the analysis of real-time industrial controllers when it is taken into account human behavior in the use of fully automated industrial systems. It is intended to develop safe controllers for these systems and make them robust against inappropriate utilizations by human operators. For the attainment of our goals it is used a case study, where, based on a IEC 60848 specification, is deduced the controller program. Further, it is elaborated the controller model, the Plant model and the Human Machine Interface Model of the automated system. The obtained results are generalized for other similar systems with the presented case study

ONE MODIFICATION OF THE CUSUM TEST FOR DETECTION EARLY STRUCTURAL CHANGES

Julia Bondarenko

The structural shifts in time series can occur as consequences of political, economic, social etc events. An ignoration of such structural changes can cause an assiciated regression model misspecification. The evidence of the parameters instability in linear models can be detected by the number of corresponding diagnostic tests. Particularly, the most famous and important of them include tests based on the F-statistic (Chow test etc), and the fluctuation tests, with the CUSUM and CUSUMQ tests of Brown, Durbin & Evans standing first on the list. In general, the basic difference between F-statistic tests and fluctiation tests lies in ability of the lasts to capture the structural breaks without precise specifying the alternative hypothesis, in contradistinction from the firsts. On the other hand, it is a well-known fact, that, in particular, CUSUM test has a poor power if the structural break point is close to the beginning and to the end of the sample period. In practice, early detection and response to outbreaks, causing the changes in a process, is highly important. In this paper, we propose a CUSUM-similar test which, due to the transformation of recursive residuals forces the detection of temporal dependence structure in linear regression model and has a larger power for the early structural breaks. Here our interest centres on the detection of stochastic dependence/trends arising in parameters of the linear model and in the errors covariance. Distribution distribution and other probabilistic characteristics of the transformed residuals are also provided.

A UNIFYING POINT OF VIEW IN THE PROBLEM OF PIO - Pilot In-the-loop Oscillations

Vladimir Răsvan, Daniela Danciu and Dan Popescu

The paper starts from the problem of PIO (Pilot-In-the-loop Oscillations), a major problem in aircraft handling and control, where the idea of the {\em feedback as hidden technology} is basic. The real phenomenon called PIO is modelled by a feedback structure where the pilot acts as one of the components of the loop and has to be modelled accordingly. PIO are in fact self-sustained oscillations and usually are divided into three convenient categories that are based on the nature of the pilot and vehicle dynamics behavior models and analysis needed for their explanation. Category I PIO are essentially linear while Category II PIO are quasi-linear and typically associated with rate limiting. Category III PIO are fully nonlinear and non-stationary. Since PIO II are mostly tackled {\em via} various robustness approaches starting from linear models, the paper strives for a unifying approach which is illustrated accordingly.

DISCRETE-EVENT SIMULATION OF A COMPLEX INTERMODAL CONTAINER TERMINAL - A Case-Study of Standard Unloading/Loading Processes of Vessel Ships

Guido Maione

The purpose of the paper is to show an application of information technology techniques to analyze the performance of a complex maritime intermodal container terminal, and to justify that changes in the system resources or container handling procedures would be necessary to guarantee the required performance in perturbed conditions. The proposed discrete-event simulation platform allows to test alternative system layouts, alternative routing strategies of container movements in order to better control all the terminal operations. The discrete-event simulation environment made available by the Arena® language is used to develop a complete simulation case-study to analyze performance indices of the currently used management policies. Results show that, especially in conditions of increased traffic volumes and reduced available stacking space, the terminal could benefit from: increase of number or different scheduling/routing policies of internal transport vehicles, increase of automation in operations to reduce times and costs.

MODEL BASED DESIGN OF NETWORKED EMBEDDED SYSTEMS - A Modeling Approach using FlexRay as an Example

Johannes Klöckner, Sven Khöler and Wolfgang Fengler

This paper presents a work in progress on a method to create system level models of networked systems in automotive applications. It introduces an example, that shows a strategy to create models, providing high flexibility in terms of interoperability, field of application, reusability and replaceability. The chosen modeling tool contains a multi-domain simulator and allows a mission and system level design. Beside the exposition of the basic architecture of the model there is a description of various model parts showing the variety of different levels of abstraction. The grade of reuseability of the developed building blocks is very high. Finally a perspective for future extensions towards a general modeling strategy for various networked applications in embedded systems is provided.

DESIGN AND IMPLEMENTATION OF A LOW-COST ATTITUDE AND HEADING NONLINEAR ESTIMATOR

Philippe Martin and Erwan Salaün

In this paper we propose a nonlinear observer (i.e. a ``filter") for estimating the orientation of a flying rigid body, using measurements from low-cost inertial and magnetic sensors. It has by design a nice geometrical structure appealing from an engineering viewpoint; it is easy to tune, computationally very economic, and with guaranteed (at least local) convergence around every trajectory. Moreover it behaves sensibly in the presence of acceleration and magnetic disturbances. We illustrate its good performance on experimental comparisons with a commercial system, and demonstrate its simplicity by implementing it on a 8-bit microcontroller.

DISCRETE-TIME ADAPTIVE REPETITIVE CONTROL - Internal Model Approach

Andrzej Krolikowski and Dariusz Horla

Repetitive control is known as one of the most effective methods to reduce repetitive errors with a known period in various practical control systems performing repetitive tasks. The application of Internal Model Control (IMC) structure for repetitive control is introduced. Two IMC-based repetitive control configurations are proposed together with their adaptive versions. A comparative simulation study is carried out for the model of a first link of the robot.

MPC FOR SYSTEMS WITH VARIABLE TIME-DELAY - Robust Positive Invariant Set Approximations

Sorin Olaru, Hichem Benlaoukli and Silviu-Iulian Niculescu

The paper deals with the control design for systems subject to constraints and affected by variable time-delay. The departing point is the construction of a predictive control law which guarantees the existence of a nonempty robust positive invariant (RPI) set with respect to the closed loop dynamics. In a second stage, an iterative algorithm is proposed in order to obtained an approximation of the maximal robust positive invariant set. The problem can be treated in the framework of piecewise affine systems due to the explicit formulations of the control law obtained via multiparametric programming.

OFF-LINE ROBUSTIFICATION OF EXPLICIT MPC LAWS - The Case of Polynomial Model Representation

Pedro Rodríguez-Ayerbe and Sorin Olaru

The paper deals with the predictive control for linear systems subject to constraints, technique which leads to nonlinear (piecewise affine) control laws. The main goal is to reduce the sensitivity of these schemes with respect to the model uncertainties and avoid in the same time a fastidious on-line optimisation which may reduce the range of application. In this idea a two stage predictive strategy is proposed, which synthesize in a first instant an analytical (continuous and piecewise linear) control law based on the nominal model and secondly robustify the central controller (the controller obtained when no constraint is active). This robustification is then expanded to all the space of the piecewise structure by means of its corresponding noise model.

PHASE LOCKED LOOPS DESIGN AND ANALYSIS

Nikolay V. Kuznetsov, Gennady A. Leonov and Svetlana S. Seledzhi

Survey of the application of PLL in computer architectures and microprocessors is given. Design of PLL in terms of phase relations is considered. Generalization of Viterbi theorem on the form of phase detector characteristic is made.

EXPERIMENTAL OPEN-LOOP AND CLOSED-LOOP IDENTIFICATION OF A MULTI-MASS ELECTROMECHANICAL SERVO SYSTEM

Usama Abou-Zayed, Mahmoud Ashry and Tim Breikin

The procedure of parameters identification of three-mass servo system using different methods is described in this paper. Both black-box and grey-box models are identified. The estimates of mechanical and electrical parameters, obtained using different data sets, are fairly stable. Experimental results show that a model consisting of three-masses connected by springs and dampers gives an acceptable description of the dynamics of the servo system. However, a lower order black-box model, identified using off-line or on-line experiments, gives better fit. The purpose of this contribution is to present experimental identification of a multi-mass servo system using different algorithms.

HYBRID WAVELET-KALMAN FILTER MULTI-SCALE SEQUENTIAL FUSION METHOD

Funa Zhou and Tianhao Tang

With the development of automation, multi-scale data fusion has become a hot research topic, however, limited by the constraint that signal to implement wavelet transform must have the length of 2q, multi-scale data fusion problem involved with non-2n sampled observation data still hasn’t been efficiently solved. In this paper, we develop a hybrid wavelet-Kalman filter multiscale sequential fusion method. First, we develop the hybrid wavelet-Kalman filter multiscale estimation method which combines the advantage of wavelet and Kalman filter to obtain the real time, recursive, multiscale estimation of the dynamic system. Then, based on this hybrid wavelet-Kalman filter, a multiscale sequential fusion method is presented. Under the hybrid wavelet-Kalman filter multiscale estimation frame, we can easily fuse information from multiple sensors sequentially without designing other complex fusion algorithm. The multiscale sequential fusion method can used to fuse non-2n sampled data just by analyzing the possible observation structure of non-2n sampled sensor to design the observation model of the stacked dynamic system. Simulation result of three sensors with sampling interval 1, 2 and 3 shows the efficiency of this method.

MULTICHANNEL EMOTION ASSESSMENT FRAMEWORK - Positive and Negative Emotional Dichotomy

Jorge Teixeira, Vasco Vinhas, Eugenio Oliveira and Luis Paulo Reis

While affective computing and the entertainment industry still maintain a substantial gap between themselves, biosignals are subject of digital acquisition through low budget technologic solutions at neglectable invasive levels preventing users from focusing their awareness in the equipment. The integration of electroencephalography, galvanic skin response and oximeter in a multichannel framework constitutes an effort in the path to identify emotional states via biosignals expression. In order to induce and detect specific emotions, gender specific sessions were defined based on the International Affective Picture System and performed in a controlled environment. Data provided was collected and visualized in real-time by the session instructor and stored for posterior processing and analysis. Results granted by distinct analysis techniques showed that high frequency EEG waves are strongly related to emotions and are a solid ground to perform accurate emotion classification. They have also given strong indications that females are more sensitive to emotion induction. On the other hand, one might conclude that the attained success levels concerning relating emotions to biosignals are extremely encouraging not only to the continuation of this research topic but also to the application of these results in domains such as multimedia entertainment, advertising and medical treatments.

ANALYSIS OF REMS GTS ERRORS DUE TO MSL ROVER AND MARTIAN ENVIRONMENT

Eduardo Sebastián, Carlos Armiens and Javier Gomez-Elvira

This paper analyses the external sources of error of the REMS GTS, a contactless instrument to measure ground temperature that is part of the payload of the NASA MSL mission to Mars. Some environment characteristics such us atmosphere opacity, Sun radiance, ground emissivity and rover IR emissions are studied, determining GTS characteristics. The article also proposes a simplified geometrical and thermal model of the rover and the environment in order to evaluate and quantify the influence in ground temperature measurements. Finally, the article summaries model simulation results and provides solutions in order to improve sensor accuracy.

MODELING AND ESTIMATION OF POLLUTANT EMISSIONS

El Hassane Brahmi, Lilianne Denis-Vidal, Zohra Cherfi, Nassim Boudaoud and Ghislaine Joly-Blanchard

Nowdays, one of the greatest problems that earth has to face up is pollution, and that is what leads European Union to make stricter laws about pollution constraints. Moreover, the European laws lead to the increase of emission constraints. In order to take into account these constraints, automotive constructors are obliged to create more and more complex systems. The use of model to predict systems behavior in order to make technical choices or to understand its functioning, has become very important during the last decade. This paper presents two stage approaches for the prediction of NOx (nitrogen oxide) emissions, which are based on an ordinary Kriging method. In the first stage, a reduction of data will take place by selecting signals with correlations studies and by using a fast Fourier transformation. In the second stage, the Kriging method is used to solve the problem of the estimation of NOx emissions under given conditions. Numerical results are presented and compared to highlight the effectiveness of the proposed methods.

SYNTHESIS METHOD OF A PN CONTROLLER USING FORBIDDEN TRANSITIONS SEQUENCES

R. Bekrar, N. Messai, N. Essounbouli, A. Hamzaoui and B. Riera

In this paper, we propose a control synthesis method for Discrete Event Systems (DES) modelled by bounded ordinary Petri Nets (PN) to treat a forbidden state problem. The considered PN is transitions controllable and markings partially measurable. The PN controller is synthesised using the forbidden transitions sequences. The latter, are deduced from the PN reachability graph and considered as a forbidden language generated by the PN model. To show the efficiency of the proposed method an illustrative example is presented.

SYNTHESIS OF VELOCITY REFERENCE CAM FUNCTIONS FOR SMOOTH OPERATION OF HIGH SPEED MECHANISMS

Robert M. C. Rayner and M. Necip Sahinkaya

The purpose of the paper is to improve the dynamic performance of a mechanism used in a packaging machine in order to run the system at higher speeds with lower vibration and noise levels. A method of synthesising a cam function for a velocity demand signal is demonstrated for a prototype mechanism and drive system. The method aims to minimise the peak to peak actuation torque requirements in order to minimise the vibration of the mechanism. First of all, experimental results are utilised to identify the drive system parameters. A dynamic simulation package is used to model the nonlinear dynamics of the mechanism. The model based synthesis of a velocity reference cam function is performed at increasing speeds of the mechanisms. The performance of the system under the proposed velocity demand cam function is compared with the conventional constant speed reference case at different running speeds.

DIRECTIONAL CHANGE IN A PRIORI ANTI-WINDUP COMPENSATORS VS. PREDICTION HORIZON

Dariusz Horla

The paper presents the correspondence in between directional change and anti-windup phenomenon with respect to a priori anti-windup compensator on the basis of MPC (simulation results include plants with not equal number of inputs and outputs). It shows what is the excess of directional change for consecutive predictions of control vectors for given prediction horizons.

A GUARANTEED STATE BOUNDING ESTIMATION FOR UNCERTAIN NON LINEAR CONTINUOUS TIME SYSTEMS USING HYBRID AUTOMATA

Nacim Meslem, Nacim Ramdani and Yves Candau

This work is about state estimation in the bounded error context for non linear continuous time systems. The main idea is to seek to estimate not an optimal value for the unknown state vector but the set of feasible values, thus to characterize simultaneously the value of the vector and its uncertainty. Our contribution resides in the use of comparison theorems for differential inequalities and the analysis of the monotonicity of the dynamical systems with respect to the uncertain variables. The uncertain dynamical system is then bracketted between two hybrid dynamical systems. We show how to obtain this systems and to use them for state estimation with a prediction-correction type observer. An example is given with bioreactors.

INSTRUMENTING BOMB DISPOSAL SUITS WITH WIRELESS SENSOR NETWORKS

John Kemp, Elena I. Gaura and James Brusey

Bomb disposal suits contain a large amount of padding and armour to protect the wearer's vital organs in the case of explosion. The combination of the heavy (roughly 40kg) suit, physical exertion, and the environment in which these suits are worn can cause the wearer's temperature to rise to uncomfortable and potentially dangerous levels during missions. This paper reports on the development of a wearable wireless sensing system suitable for deployment in such manned bomb disposal missions. In its final form, the system will be capable of making in-network autonomous decisions related to the actuation of cooling within the suit, in order to increase the comfort of the wearer. In addition, it will allow an external observer to remotely monitor the health and comfort of the operative. Laboratory experiments with the instrumented suit show how skin temperature varies differently for different skin sites, motivating the need for multiple, distributed sensing. The need for timely application of in-suit cooling is also shown, as well as the importance of monitoring the overall health of the wearer of the suit.

TOWARDS A STANDARDIZED AND EXTENSIBLE MECHANISM FOR ROBOT DEVICE INTEGRATION - A XIRP-based Approach and Test Bed Implementation

Fan Dai and Joachim Unger

In industrial robot automation, the integration of intelligent peripheral devices becomes more and more important. But there is no standardized mechanism to setup the communication interface between them and to configure the usage of the device information for the robot applications. This makes the integration task often very tedious and time consuming. XIRP – the XML-based Interface for Robots and Peripherals is a recommendation that was published by the German standardization institute DIN in 2006. It specifies a standardized mechanism and the corresponding communication protocol for robot device integration. Our experiences with XIRP-based implementations have shown its big potential to support robotics PnP on the communication and configuration level. But at the same time, we found some insufficiencies and weaknesses of the specification. This paper introduces our approach for a revised XIRP concept, and discusses our experiences made on test-bed implementations.

PLUG-AND-PRODUCE TECHNOLOGIES REAL-TIME ASPECTS - Service Oriented Architectures for SME Robots and Plug-and-Produce

Klas Nilsson and Matthias Bengel

Plug-and-Produce (with the meaning that devices can be plugged in without any manual configurations needed) is an attractive paradigm for manufacturing systems, and in particular for Small and Medium Enterprises (SMEs) that do not have the expertise of system integrators but do need to be able to reconfigure their systems by themselves. One approach for loosely (in terms of timing) coupled devices is that of Service-Oriented Architectures (SOA). As can be understood from developments with multiple robot arm and online operator interactions, future applications will in some cases need real-time guarantees for performing services. That includes both real-time communication and the need to perform services with a predictable timing. A review of available technologies and inherent limitations of distributed computing leads to the conclusion that the standard SOA approach based on process oriented (like for RPCs and web services) calls similar to distributed object orientation will not be practically useful. Instead, a data or state centric approach should be adapted together with one-way message-based communication.

AUTOMATIC GENERATION OF EXECUTABLE CODE FOR A ROBOT CELL USING UPNP AND XIRP

Martin Naumann

This paper deals with the concept of a control architecture for robot cells that enables Plug’n’Produce according to Plug’n’Play in the office world. To achieve this, the cell controller needs special functionality located in a software module called “P’n’P-Module”. This module takes as input descriptions of devices and processes. These descriptions are then automatically evaluated in order to offer the user device-independent high-level commands to define a task for the robot cell. Based on this task definition executable code has to be generated. The focus of this paper lies on the descriptions and algorithms necessary to generate executable code. The presented method will be realized as a testbed within a bin picking cell using UPnP and XIRP.

TOWARD ONTOLOGIES AND SERVICES FOR ASSISTING INDUSTRIAL ROBOT SETUP AND INSTRUCTION

Mathias Haage, Anders Nilsson and Pierre Nugues

Achieving rapid, intuitive and error-free robot setup and instruction is a challenge. We present our work towards an assistive infrastructure for robot setup and instruction. Results from continuing development of a system for automatic generation of multi-modal dialogue interaction from process and product ontologies are presented, exemplified by digital paper and voice. Ongoing work for developing a system for calibration support from equipment and process ontologies is presented.

COMMUNICATION, CONFIGURATION, APPLICATION - The Three Layer Concept for Plug-and-Produce

Uwe E. Zimmermann, Rainer Bischoff, Gerhard Grunwald, Georg Plank and Detlef Reintsema

The Plug-And-Play is a synonym for the simple use of computer systems in office applications. This appealing idea also emerges in the branches of robotics and automation. But due to their specific technical and application driven requirements i.e. real-time, determinism, safety… a simple taking over of the technology is not sufficient. Plug-and-Produce extends the “easy to use” for applications in robotics and automation. This will lead to a dramatically reduction of set-up times of work-cells. In order to fulfil the various requirements a three layered Plug-and-Produce architecture is presented. The communication layer addresses all topics regarding the bus-system level; the configuration layer is responsible for the control and operation system level; and the application layer addresses the needs of the user and system programmer. A prototypical implementation is also presented.

PLUG-AND-PRODUCE TECHNOLOGIES - On the Use of Statecharts for the Orchestration of Service Oriented Industrial Robotic Cells

Germano Veiga and J. Norberto Pires

Programming industrial robotic workcells is a challenging task, namely because it means dealing with several types of machines, mange the data flow between them and orchestrate their basic functionality into a working program. In this work service oriented architectures are used for the task of programming robotic workcells along with managing the communication between cell components, and a statechart model engine is implemented to orchestrate the system logic. The objective of this paper is to focus in merging service oriented architectures with StateCharts XML, and in evaluating that robotic workcell programming approach using a simple laboratory test bed.

POTENTIAL FIELD BASED INTEGRATED EXPLORATION FOR MULTI-ROBOT TEAMS

Miguel Juliá, Arturo Gil, Luis Payá and Oscar Reinoso

In this paper we present an approach for multi-robot cooper- ative exploration based on the potential field generated by several basic behaviours. When an unknown environment is explored the uncertainty in the localization normally grows, this fact may cause the failure of the Simultaneous Localization and Mapping (SLAM) algorithm, and thus constructing an useless and inaccurate map. The exploration algorithm described here considers the current knowledge of the environment, the location of the robots and the uncertainty in their positions in order to return to previously explored areas when it is needed. These actions definitely help the SLAM algorithm to build a precise map. Several sim- ulations are presented that demonstrate the validity of the approach.

A GENERIC ARCHITECTURE FOR A COMPANION ROBOT

Bas R. Steunebrink, Nieske L. Vergunst, Christian P. Mol, Frank P. M. Dignum, Mehdi Dastani and John-Jules Ch. Meyer

Despite much research on companion robots and affective virtual characters, a comprehensive discussion on a generic architecture is lacking. We compile a list of possible requirements of a companion robot and propose a generic architecture based on this list. We explain this architecture to uncover issues that merit discussion. The architecture can be used as a framework for programming companion robots.

ROBOTIC SOCCER: THE GATEWAY FOR POWERFUL ROBOTIC APPLICATIONS

Luiz A. Celiberto Junior and Jackson P. Matsuura

From the RoboCup goal of having a fully autonomous humanoid soccer team, it is possible to see many applications of the research in the Humanoid Soccer, such as the development of mechanical legs and arms and exoskeletons. The onboard vision algorithms for multi target tracking and the cooperative decision making of some Soccer Leagues can be used in squadrons of autonomous vehicles in a variety of missions. The algorithms for image processing of the Small Size League can be used in aerial or satellite images to track vehicles. The Simulation League allows the development of many intelligent agents applications. The formations and team play positioning of the Simulation League can be used to optimize the positioning of a squadron of autonomous vehicles. The research of Robotic Soccer fosters and strengthens the research in Robotics, allowing and contributing to the development of many powerful applications which can great benefit the mankind.

TRILATERATION LOCALIZATION FOR MULTI-ROBOT TEAMS

Paul M. Maxim, Suranga Hettiarachchi, William M. Spears, Diana F. Spears, Jerry Hamann, Thomas Kunkel and Caleb Speiser

The ability of robots to quickly and accurately localize their neighbors is extremely important for robotic teams. Prior approaches typically rely either on global information provided by GPS, beacons and landmarks, or on complex local information provided by vision systems. In this paper we describe our trilateration approach to multi-robot localization, which is fully distributed, inexpensive, and scalable. Our prior research focused on maintaining multi-robot formations indoors using trilateration. This paper pushes the limits of our trilateration technology by testing formations of robots in an outdoor setting at larger inter-robot distances and higher speeds.

USING ROBOTIC SYSTEMS IN A SMART HOUSE FOR PEOPLE WITH DISABILITIES

Viorel Stoian and Cristina Pana

We present in this paper several ideas about the usability of the robotic arms and mobile robots as an assistive technology in a smart house where people with disabilities daily live. First, psychological and social aspects of smart home technology are presented and after that the modularity and standardization processes are discussed. Next we propose a smart house plan, equipped with a mobile robot which has a manipulator arm. This robotic system is used to help vulnerable persons, the handicapped men vehicle seat being equipped with a robotic arm which can manipulate objects by a hyper-redundant gripper. For the control of the processes in the smart house, we propose a hierarchical control system and for the mobile robot we use the artificial potential field method. Also, this paper points out the edutainment concept (EDUcation and enterTAINMENT) by robotics. Finally, some applications are presented.

COLLABORATION VS. OBSERVATION: AN EMPIRICAL STUDY IN MULTIAGENT PLANNING UNDER RESOURCE CONSTRAINT

Emmanuel Benazera

A team of robots and an exploratory mission are modeled as a multiagent planning problem in a decentralized decision theoretical framework. In this application domain, agents are constrained by resources such as their remaining battery power. In this context, there is an intrinsic relation between collaboration, computation and the need for the agents to observe their resource level. This paper reports on an empirical study of this relationship.

CONCEPTS FOR AUTONOMOUS COMMAND AND CONTROL

Fernando Escobar and John Mcdonnell

The new Department of Defense (DOD) transformational doctrines for future battlefield operations emphasizes the need to more aggressively pur-sue program developments with unmanned systems technologies. Currently, there are ongoing Battle Experiments testing and assessing the operational per-formance of these technologies. These experiments in turn are uncovering cur-rent and future capability gaps that need to be fulfilled with aggressive research, engineering, test and evaluation. The Innovation Center at SPAWAR Systems Center, San Diego, has established a research and development process to better address Future Naval Capability gaps in the areas of both, Intelligent Autonomy and Autonomous Command and Control for Unmanned Systems. In this paper we report our research on two important components concepts for AC2: 1) Au-tonomous Resource Allocation, 2) Autonomy and Commanders Intent, and 3) A discussion on Self organizing C2

Forecasting Internet Traffic by Neural Networks Under Univariate and Multivariate Strategies

Paulo Cortez, Miguel Rio, Pedro Sousa and Miguel Rocha

By improving Internet traffic forecasting, more efficient TCP/IP traffic control and anomaly detection tools can be developed, leading to economic gains due to better resource management. In this paper, Neural Networks (NNs) are used to predict TCP/IP traffic for 39 links of the UK education and research network, under univariate and multivariate strategies. The former uses only past values of the forecasted link, while the latter also uses the traffic from neighbor links of the network topology. Several experiments were held by considering hourly real-world data. The Holt-Winters method was also tested in the comparison. Overall, the univariate NN approach produces the best forecasts for the backbone links, while a Dijkstra based NN multivariate strategy is the best option for the core to subnetwork links.

Transient IC Engine Monitoring under Temperature Changes using an AANN

Xun Wang, George W. Irwin, Geoff McCullough, Neil McCullough and Uwe Kruger

This paper reports on non-linear principal component analysis for fault detection on an internal combustion (IC) engine. An auto-associative neural network (AANN) model is built from transient engine data collected under varying atmospheric conditions. The experimental data used for modelling was collected for two different drive cycles, the Identification Cycle and the New European Drive Cycle. The key issue here is to decide which data should be used for training the neural network to produce good fault detection generalisation under different atmospheric conditions and with a different drive cycle. This is achieved successfully, with the Q monitoring statistic indicating an absence of unwanted false alarms under fault-free operation, along with successful detection of air leaks of varying magnitude in the inlet manifold.

Combining Selective-Presentation and Selective-Learning-Rate Approaches for Neural Network Forecasting of Stock Markets

Kazuhiro Kohara

We have investigated selective learning techniques for improving the ability of back-propagation neural networks to predict large changes. We previously proposed the selective-presentation approach, in which the training data corresponding to large changes in the prediction-target time series are presented more often, and selective-learning-rate approach, in which the learning rate for training data corresponding to small changes is reduced. This paper proposes combining these two approaches to achieve fine-tuned and step-by-step selective learning of neural networks according to the degree of change. Daily stock prices are predicted as a noisy real-world problem. Combining these two approaches further improved the performance.

Receptor Response and Soma Leakiness in a Simulated Spiking Neural Controller for a Robot

David Bowes, Rod Adams, Lola Cañamero, Volker Steuber and Neil Davey

This paper investigates different models of leakiness for the soma of a simulated spiking neural controller for a robot exhibiting negative photo-taxis. It also investigates two models of receptor response to stimulus levels. The results show that exponential decay of ions across the soma and of a receptor response function where intensity is proportional to intensity is the best combination for dark seeking behaviour.

Comparison of Defuzzification Methods: Automatic Control of Temperature and Flow in Heat Exchange

Carlos A. Cosenza, Alvaro J. Rey Amaya, Omar Lengerke, Max Suell Dutra and Magda J. M. Tavera

The objective of this work is to analyze the behavior of the traditional control and the fuzzy control, applying them in the flow and temperature control to the load of current of a heat exchanger, as well as the analysis of different methods of defuzzification, utilized just as itself this carrying out the fuzzy control. Acting on the structure of the fuzzy controller some changes of form are carried out such that this tune in to be able to obtain the answer but optimum. In the same way proceeds on the traditional controller, and in this way comparisons on these two types of controls are established. Inside the changes that are carried out on the fuzzy controller this form of defuzzification the information, that is to say the methods are exchanged defuzzification in order then to realize comparisons on the behavior of each one of these.

NN and Hybrid Strategies for Speech Recognition in Romanian Language

Corneliu-Octavian Dumitru and Inge Gavat

In this paper we present results obtained with learning structures more “human likely” than the very effective and widely used hidden Markov model. Good results were obtained with simple artificial neural networks like the multilayer perceptron or the Kohonen maps. Hybrid structures have proven also their efficiency, the neuro-statistical hybrid applied enhancing the digit recognition rate of the initial HMM. Also fuzzy variants of the MLP and HMM gave good results in the tested tasks of vowel recognition.

An Authentication Protocol for Wireless Ad Hoc Networks with Embedded Certificates

Robert E. Hiromoto and J. Hope Forsmann

Wireless ad hoc networks may be configured as a fixed topology of sensors or allowed to migrate as mobile nodes. The flexibility of these networks, therefore, provides opportunities for their deployment in real-time and in adverse situations as encountered in civil and military applications. These advantages are, unfortunately, curtailed by the unconstrained nature of these networks in providing a trusted level of connectivity. The establishment of secret keys and the authentication of trusted ad hoc group nodes are essential elements for a secure network. In this paper, we develop an authentication protocol for wireless ad hoc networks that is derived from a canonical splitting of timeand frequency-space (channel) over which information propagates under the constraint of a collision-avoidance protocol.

ZISC Neuro-Computer for Task Complexity Estimation in T-DTS Framework

Ivan Budnyk, Abdennasser Chebira and Kurosh Madani

This paper presents the implication of new approach based on ZISC © IBM ® neuro-computer for T-DTS complexity estimating main module. The goal of T-DTS is to build a tree neural structure following the paradigm “divide and conquer”. The aim of out work is to increase the T-DTS quality of the classifica-tion performance based on ZISC complexity estimator.

Learning and Evolution in Artificial Neural Networks: A Comparison Study

Eva Volna

This paper aims at learning and evolution in artificial neural networks. Here is presented a system evolving populations of neural nets that are fully connected multilayer feedforward networks with fixed architecture solving given tasks. The system is compared with gradient descent weight training (like backpropagation) and with hybrid neural network adaptation. All neural networks have the same architecture and solve the same problems to be able to be compared mutually. In order to test the efficiency of described algorithms, we applied them to the Fisher's Iris data set that is the bench test database from the area of machine learning.

Codesign strategy based upon Takagi Sugeno control Design and Real-Time Computing Integration

Héctor Benítez-Pérez

Nowadays the idea of network control systems design considering the restriction results from schedulling analysis becomes a challenge based upon the persepctive of codesign point view since both analytic tools are pursued. A clear strategy is to define in cascade mode the scheduling analysis and afterwards the stability analysis of the respective control strategy. However, any modification in both structures has an integrated impact which is necessary to measure. In that respect the use of time delay impact is a suitable strategy to be followed and is explored in this paper. The use of codesign is to pursuit as a two objective strategy the definition of a valid metric that represents the effects in both, following the idea that stability analysis is affected according to the schedullability analysis. In both analysis a relaxation at the local conditions is feasible but it will have a global cost giving a non valuable approximation.

End Milling: A Neural Approach for Defining Cutting Conditions

Orlando Duran, Nibaldo Rodriguez and Luiz Airton Consalter

The purpose of this paper is to present a new adaptive solution based on a feed forward neural network (FNN) in order to improve the task of selecting cutting conditions for milling operations. From a set of inputs parameters, such as work material, its mechanical properties, and the type of cutting tool, the system suggests feed rate and cutting speed values. The four main issues related to the neural network-based techniques, namely, the selection of a proper topology of the neural network, the input representation, the training method and the output format are discussed. The proposed network was trained using a set of inputs parameters provided by cutting operations manuals and tool manufacturers catalogues. Some tests and results show that adaptative solution proposed yields performance improvements. Finally, future work and potential applications are outlined.

Adaptive Electrical Signal Post-Processing in Optical Communication Systems

Yi Sun, Alex Shafarenko, Rod Adams, Neil Davey, Brendan Slater, Ranjeet Bhamber, Sonia Boscolo and Sergei K. Turitsyn

Improving bit error rates in optical communication systems is a difficult and important problem. The error correction must take place at high speed and be extremely accurate. We show the feasibility of using hardware imple- mentable machine learning techniques. This may enable some error correction at the speed required.

Distributed Mission and Contingency Management for the DARPA Urban Challenge

Tichakorn Wongpiromsarn and Richard Murray

We present an approach that allows mission and contingency management to be achieved in a distributed and dynamic manner without any central control over multiple software modules. This approach comprises two key elements---a mission management subsystem and a Canonical Software Architecture (CSA) for a planning subsystem. The mission management subsystem works in conjunction with the planning subsystem to dynamically replan in reaction to contingencies. The CSA ensures the consistency of the states of all the software modules in the planning subsystem. System faults are identified and replanning strategies are performed distributedly in the planning and the mission management subsystems through the CSA. The approach has been implemented and tested on Alice, an autonomous vehicle developed by the California Institute of Technology for the 2007 DARPA Urban Challenge.

A Solution to the Parallel Parking Problem

Sinan Öncü and Mürvet Kırcı

Nowadays parts of a car have been designed form in which make us easy driving. One of the driving problems is parallel parking. This study gives a solution with an algorithm to the parallel parking problem. Simulation of the solution including all cases in the parallel parking has been made based on this algorithm. Implementation of the simulation has been made as a robot car. The approach has been integrated into an automated parking system, and implemented a modified car. It shows the potential to be integrated into automobiles.

Electronic Horizon - Providing Digital Map Data for ADAS Applications

Christian Ress, Aria Etemad, Detlef Kuck and Julián Requejo

The number of navigation devices in a vehicle has increased tremendously during the last years, especially with the rapid introduction of mobile devices. The digital maps of these systems contain a lot of valuable information that can be used for other features besides route guidance as well. The area of potential applications reaches from driver information and warning systems up-to comfort and active safety applications, so-called Advanced Driver Assistance Systems (ADAS). Since built-in vehicle sensors are limited to a relatively short range, digital map data can be used as a virtual sensor to "look" much further into the direction of the vehicle's path. The digital map contains attributes that are attached to the road segments describing e.g. road geometry, functional road class, number of lanes, speed limits, traffic signs, etc. This data is extracted from the map and delivered on a vehicle bus system using a well specified interface as the so-called Electronic Horizon. European automotive industry has teamed up in the ADASIS Forum to develop a common standardized interface. Ford Research & Advanced Engineering Europe is contributing to ADASIS and has developed a prototype system providing Electronic Horizon, which has successfully been tested and validated for Lane Keeping Assistance as one application example.

Situational Reasoning for Road Driving in an Urban Environment

Noel E. Du Toit, Tichakorn Wongpiromsarn, Joel W. Burdick and Richard M. Murray

Robot navigation in urban environments requires situational reasoning. Given the complexity of the environment and the behavior specified by traffic rules, it is necessary to recognize the current situation to impose the correct traffic rules. In an attempt to manage the complexity of the situational reasoning subsystem, this paper describes a finite state machine model to govern the situational reasoning process. The logic state machine and its interaction with the planning system are discussed. The approach was implemented on Alice, Team Caltech’s entry into the 2007 DARPA Urban Challenge. Results from the qualifying rounds are discussed. The approach is validated and the shortcomings of the implementation are identified.

Using Predictive Digital Map Data to Enhance Vehicle Safety and Comfort

Julián Requejo, Christian Ress, Aria Etemad and Detlef Kuck

Navigation systems based on GPS and digital maps have become extremely popular in passenger and commercial vehicles during the last years. The accuracy and amount of information contained in digital maps is constantly evolving, offering a tremendous amount of knowledge about the road network. In addition to providing driving directions, this information may be used on a wide range of technologies. One of these is the so-called Electronic Horizon, a digital map-based application that helps to overcome the physical limits of certain vehicle sensors, such as radar and vision systems. This is accomplished by predicting where the driver is heading, and subsequently extracting from the digital maps information about the predicted path. Speed limits, road quality, slope, and other road attributes predicted along the most-likely-path is then presented via a common standard interface to other applications, ranging from environmental to comfort and safety functions. The goal of this paper is to show the benefit of predictive map data for safety and comfort applications inside the vehicle. It introduces the reader to the electronic horizon, the most-likely path concept, and gives an overview of some of its applications that are actively being researched by the automotive industry.

Floating Car Observer – Approaches for Traffic Management Strategies by Analysing Oncoming Vehicles

Franziska Wolf, Sebastian Naumann, Christoph Engel and René Schönrock

Abstract. For traffic management systems, the knowledge of urban traffic conditions is essential. The strategy of the Floating Car Observer (FCO) is the col-lection of traffic data via moving traffic sensors. The data of oncoming cars and trucks are detected using a traveling public transport vehicle. Different acquisition strategies are evaluated to establish a low cost application, capable of real time usage. Using the reflection of the infra-red emitter on number plates, traffic data information about the speed and the average density of oncoming traffic is acquired. The properties of the hardware prototype and the implementation of the software strategies are discussed and first research results are presented.

A Predictive Controller for Object Tracking of a Mobile Robot

Xiaowei Zhou, Plamen Angelov and Chengwei Wang

In this paper a predictive controller for real-time target tracking in mobile robotics is proposed based on adaptive/evolving Takagi-Sugeno fuzzy systems, eTS. The predictive controller consists of two modules; i) a conventional fuzzy controller for robot motion control, and ii) a modelling tool for estimation of the target movements. The prediction of target movements enables the controller to be aware and to respond to the target movement in advance. Successful prediction will minimise the response delay of the conventional controller and improve the control quality. The model learning using eTS is fully automatic and performed ‘on fly’, ‘from scratch’. Data are processed in ‘one-pass’ manner, therefore it requires very limited computational resource and is suitable for on-board implementation on the mobile robots. Predictions are made in real-time. The same technique also has the potential to be used in the process control. Two reference controllers, a controller based on the Mamdani-Type fuzzy rule-base, and a controller based on the simple linear model, are also implemented in order to verify the proposed predictive controller. Experiments are carried out with a real mobile robot Pioneer 3DX. The performance of the three controllers is analyzed and compared.

Intelligent Refueling Advisory System

Erica Klampfl, Oleg Gusikhin, Kacie Theisen, Yimin Liu and T. J. Giuli

Recent advances in wireless communication technologies have led to numerous new developments that take advantage of network access, ranging from real-time information delivery essential for many driving decisions to harvesting off-board computing power for remote vehicle diagnostics. Specifically, with the ever increasing fuel cost, there is growing popularity of services that provide information to drivers on current gas prices and alerts on upcoming changes to gas prices. This paper demonstrates how to take currently available technology one step further by providing a proactive refueling advisory system based on minimizing fuel costs over routes and time. The system integrates vehicle data, a navigation system, and internet connectivity to supplant the existing vehicle low fuel warning with a comprehensive decision support system on refueling choices.

Discrete-Time Drift Counteracting Stochastic Optimal Control and Intelligent Vehicle Applications

Ilya Kolmanovsky and John Michelini

In this paper we present a characterization of a stochastic optimal control in the problem of maximizing expected time to violate constraints for a nonlinear discrete-time system with a measured (but unknown in advance) disturbance modeled by a Markov chain. Such an optimal control may be viewed as providing drift counteraction and is, therefore, referred as the drift counteracting stochastic optimal control. The developments are motivated by an application to an intelligent vehicle which uses an adaptive cruise control to follow a randomly accelerating and decelerating vehicle. In this application, the control objective is to maintain the distance to the lead vehicle within specified limits for as long as possible with only gradual (small) and smooth accelerations and decelerations of the follower vehicle so that driver comfort can be increased and fuel economy can be improved.