2010 Events:
Note: the linked titles for some events are the presentations speakers provided which can be viewed online or downloaded.
December 9, 2010: "Autonomy: From Outer to Inner Space Deep Ocean Exploration using NASA Technology" by Dr. Kanna Rajan, Monterey Bay Aquarium Research Institute (MBARI)
Abstract: Ocean Sciences the world over is at a cusp, with a move from the Expeditionary to the Observatory mode of doing science. Recent policy decisions in the United States, are pushing the technology for persistent observation and sampling which hitherto had been either economically unrealistic or unrealizable due to technical constraints. With the advent of ocean observatories, a number of key technologies have however proven to be promising for sustained ocean presence. In this context robots will need to be contextually aware and respond rapidly to evolving phenomenon, especially in coastal waters due to the diversity of atmospheric, oceanographic and land-sea interactions not to mention the societal impact they have on coastal communities. They will need to respond by exhibiting scientific opportunism while being aware of their own limitations in the harsh oceanic environment. Current robotic platforms however have inherent limitations; pre-defined sequences of commands are used to determine what actions the robot will perform and when irrespective of the context. As a consequence not only can the robot not recover from unforeseen failure conditions, but they're unable to significantly leverage their substantial onboard assets to enable scientific discovery.
To mitigate such shortcomings, we are developing deliberative techniques to dynamically command Autonomous Underwater Vehicles (AUV). Our effort is aimed to use a blend of generative and deliberative Artificial Intelligence Planning and Execution techniques to shed goals, introspectively analyze onboard resources and recover from failures. In addition we are working on Machine Learning techniques to adaptively trigger science instruments that will contextually sample the seas driven by scientific intent. The end goal is towards unstructured exploration of the subsea environments that are a rich trove of problems for autonomous systems. Our approach spans domains and not unduly specific to the ocean domain; the developed system is being used for a terrestrial personal robot at a Silicon Valley startup and will soon be on a Planetary rover testbed in Europe. Our work is a continuum of efforts from research at NASA to command deep space probes and Mars rovers, the lessons of which we have factored into the oceanic domain. In this talk I will articulate the challenges of working in this hostile underwater domain, lay out the differences and motivate our architecture for goal-driven autonomy on AUV's.
Bio: Kanna is the Principal Researcher in Autonomy at the Monterey Bay Aquarium Research Institute (https://www.mbari.org) a privately funded non-profit Oceanographic institute which he joined in October 2005. Prior to that he was a Senior Research Scientist for the Autonomous Systems and Robotics Area at NASA Ames Research Center Moffett Field, California. At Ames, he balanced programmatic and technical responsibilities. He was the Principal Investigator of the MAPGEN Mixed-Initiative Planning effort to command and control the Spirit and Opportunity rovers on the surface of the Red Planet. MAPGEN continues to be used to this day, twice daily in the mission-critical uplink process at the Jet Propulsion Laboratory in Pasadena. Kanna was one of the six principals of the Remote Agent Experiment (RAX) team, which designed, built, tested and flew the first closed-loop AI based control system on a spacecraft. The RA was the cowinner of NASA's 1999 Software of the Year, the agency's highest technical award (https://ic.arc.nasa.gov/projects/remote-agent).
His interests are in automated Planning/Scheduling, modeling and representation for real world planners and agent architectures for Distributed Control applications. Prior to joining NASA Ames, he was in the doctoral program at the Courant Institute of Math Sciences at New York University. Prior to that he was at the Knowledge Systems group at American Airlines, helping build a Maintenance Routing scheduler (MOCA), which continues to be used by the airline 365 days of the year.
MAPGEN has been awarded NASA's 2004 Turning Goals into Reality award under the Administrators Award category, a NASA Space Act Award, a NASA Group Achievement Award and a NASA Ames Honor Award. Kanna is the recipient of the 2002 NASA Public Service Medal and the First NASA Ames Information Directorate Infusion Award also in 2002. In Oct 2004, JPL awarded him the NASA Exceptional Service Medal for his role on the Mars Exploration Rovers misson. He was the Co-chair of the 2005 International Conference on Automated Planning and Scheduling (ICAPS), Monterey California and till recently the chair of the Executive Board of the International Workshop on Planning and Scheduling for Space. He continues to serve on review panels for NASA, the Italian Space Agency and European Space Agency.
Dr. Rajan can be reached at https://www.mbari.org/staff/kanna.
December 1, 2010: "Guided Tour of NASA Ames' Vertical Motion Simulator" by Rodger Mueller, NASA Ames
Abstract: This tour for IEEE-CSS members offers a rare view of NASA's Vertical Motion Simulator (VMS). The VMS is a unique flight simulation complex that provides researchers with exceptional tools to explore, define, and solve issues in both aircraft and spacecraft design. It offers fast and cost-effective solutions using real-time piloted simulation, realistic sensory cues, and the greatest motion range of any flight simulator in the world.
For additional details please visit the VMS website.
Bio: Rodger Mueller is a licensed Control System Engineer who began his career at Ames Research Center as a contractor upon graduation from Heald Engineering College in 1965. Initially, he was assigned the task of setting up the EAI 231R-V analog computers for flight simulations and tasked with operation of the Power Spectral Density program. During this period, he analyzed and modified the Link Pilot Control Loader simulation system for current flight simulations. Later in the decade, he developed the first analog computer pilot force-feel program at NASA Ames Research Center for the newly acquired McFadden Pilot Control Loaders.
In the early 1970s, he developed the EAI 8812 analog computer programs for the Saturn V First Stage and the Vertical/Short Takeoff and Landing Optimization simulations. For twelve years, Mr. Mueller also supervised a hardware design and fabrication section along with creating analog and logic circuit designs.
He developed the last analog computer pilot force-feel program for the McFadden Pilot Control Loaders in the early 1980s. After becoming a NASA employee in 1984, Mr. Mueller also developed an analog program for the automated dynamic checkout of the Flight Simulator for Advanced Aircraft (FSAA). He led a team that developed a single point grounding system for the Vertical Motion Simulator (VMS) to correct for ground loops and noise problems that were severe enough to prevent operation of the VMS. He continued his pilot control loader support with the specification of new transducers and the development of tuning methods for optimizing performance to further enhance the McFadden pilot controls.
In 2004, he developed a digital computer pilot force-feel program to replace the analog computer program. This new program provides more extensive force-feel functions and additional safety features, yet is still flexible enough to respond to changing customer requirements. During this same period, he developed and implemented a technique for compensating McFadden Pilot Control Loader pilot force measurements for inertia and gravity force effects to give accurate pilot force measurements.
Awards:
- NASA Ames Research Center 2003 Engineer of the Year
- NASA Ames Research Center Best First Paper for 2008
- 2010 AIAA de Florez Award for Flight Simulation.
November 18, 2010: "Robot control for medical applications and hair transplantation" by Dr. John Tenney, Restoration Robotics, Inc.
Abstract: Medical device applications have proven to be fertile ground for innovative robotic control solutions. In this talk, Dr. John Tenney of Restoration Robotics, Inc., describes the wide range of medical device robotic applications. He will then discuss the application of both force control and 3-D stereo visual servoing as part of the real-time control system created by his company, Restoration Robotics.
Bio: John Tenney is Director of Research at Restoration Robotics, Inc., a medical device startup that is designing a hair transplantation robotic system. Between 2004 and 2007, he served as Chief Software Architect at Adept Technology, where he led design and implementation of a new generation of their control system. In 1996, he co-founded Commotion Technology, which developed a VxWorks and PC-based robot control package. He became Director of Motion Control at PRI-Brooks Automation when Commotion was acquired in 2000. Dr. Tenney earned his PhD in Mechanical Engineering from Berkeley in 1996, his MS from Stanford in 1986, and his BS from MIT in 1982.
September 16, 2010: "Patent Strategies for Entrepreneurs and Innovative Thinkers" by Dave Stevens, Stevens Law Group, P.C.
Abstract: This presentation from a legal expert outlines general principles of intellectual property (IP) protection for various technologies, and will provide practical strategic planning tools and roadmaps for different types of companies and ventures. Case studies will provide working examples of IP roadmaps and strategies that have worked for successful startup ventures and fortune 500 companies. Ample time will be reserved for group questions, and also offline discussions afterwards.
Bio: Dave Stevens is a principle in the IP firm Stevens Law Group, PC. He has practiced IP law as a litigator, negotiator, and company builder for over 20 years. Dave specializes in startup company formation, and serves as legal counsel to numerous high tech startup companies. He is an industry expert on IP procurement and monetization, and lectures around the world on these and other global IP topics as they relate to various locales, technologies and legal fields. Dave can be reached at Dave.stevens@stevenslawgroup.com.
March 18, 2010: Joint meeting with SCV-RAS "'Cognitive' Memory and its Applications" by Dr. Bernard Widrow, Professor of Electrical Engineering, Stanford University
Abstract: Regarding the workings of the human mind, memory and pattern recognition seem to be intertwined. You generally do not have one without the other. Taking inspiration from life experience, a new form of computer memory has been devised. Certain conjectures about human memory are keys to the central idea. The design of a practical and useful "cognitive" memory system is contemplated, a memory system that may also serve as a model for many aspects of human memory. The new memory does not function like a computer memory where specific data is stored in specific numbered registers and retrieval is done by reading the contents of the specified memory register, or done by matching key words as with a document search. Incoming sensory data would be stored at the next available empty memory location, and indeed could be stored redundantly at several empty locations. The stored sensory data would neither have key words nor would it be located in known or specified memory locations. Sensory inputs concerning a single object or subject are stored together as vectors in a single "file folder" or "memory folder". When the contents of the folder are retrieved, sights, sounds, tactile feel, smell, etc., are obtained all at the same time. Sensor fusion is a memory phenomenon. The sensory signals are not fused, but they are simply recorded together in the same folder and retrieved together. Retrieval would be initiated by a prompt signal from a current set of sensory inputs or patterns. A search through the memory would be made to locate stored data that correlates with or relates to the present real-time sensory inputs. The search would be done by a retrieval system that makes use of auto-associative artificial neural networks. Applications of cognitive memory systems have been made to visual aircraft identification, aircraft navigation, and human facial recognition. Other applications to speech recognition and control systems are being explored.
Bio: Bernard Widrow received the S.B., S.M., and Sc.D. degrees in Electrical Engineering from the MIT in 1951, 1953, and 1956, respectively. He joined the MIT faculty and taught there from 1956 to 1959. In 1959, he joined the faculty of Stanford University, where he is currently Professor of Electrical Engineering.
He began research on adaptive filters, learning processes, and artificial neural models in 1957. Together with M.E. Hoff, Jr., his first doctoral student at Stanford, he invented the LMS algorithm in the autumn of 1959. Today, this is the most widely used learning algorithm, used in every MODEM in the world. He has continued working on adaptive signal processing, adaptive controls, and neural networks since that time.
Dr. Widrow is a Life Fellow of the IEEE and a Fellow of AAAS. He received the IEEE Centennial Medal in 1984, the IEEE Alexander Graham Bell Medal in 1986, the IEEE Signal Processing Society Medal in 1986, the IEEE Neural Networks Pioneer Medal in 1991, the IEEE Millennium Medal in 2000, and the Benjamin Franklin Medal for Engineering from the Franklin Institute of Philadelphia in 2001. He was inducted into the National Academy of Engineering in 1995 and into the Silicon Valley Engineering Council Hall of Fame in 1999.
Dr. Widrow is a past president and member of the Governing Board of the International Neural Network Society. He is associate editor of several journals and is the author of over 125 technical papers and 21 patents. He is co-author of Adaptive Signal Processing and Adaptive Inverse Control, both Prentice-Hall books. A new book, Quantization Noise, was published by Cambridge University Press in June 2008.
February 18, 2010: "Modeling and Optimization in Traffic Flow Management" by Dr. Banavar Sridhar, NASA Senior Scientist
Abstract: A safe and efficient aviation industry is vital to the global economy. The growing traffic demand, rise in oil prices, delays in building new runways and security issues are putting pressures on the system to evolve from the current procedure-based human-centered system to a more flexible system with higher levels of automation. Traffic Flow Management (TFM) is the efficient organization of traffic flows to meet demand taking into account capacity constraints at airports and in en route airspace. TFM involves thousands of aircraft and several layers of decision-makers scattered between the FAA, Airlines and other users of airspace. Several types of uncertainties are pervasive in the system. This talk explores the complexity and richness of the problems in TFM by considering research in four different areas:
- Characteristics of the TFM Network;
- Aggregate Models for TFM;
- Relationship between weather, traffic and delay;
- Optimization. Current approaches towards finding best solutions to these problems are discussed.
Bio: Banavar Sridhar received the B.E. degree in electrical engineering from the Indian Institute of Science and the M.S. and Ph.D. in electrical engineering from the University of Connecticut. He worked at Systems Control, Inc., Palo Alto, Ca and Lockheed Palo Alto Research Center before joining NASA Ames Research Center in 1986. He was recently appointed as NASA Senior Scientist for Air Transportation Systems. His research interests are in the application of modeling and optimization techniques to aerospace systems. Dr. Sridhar received the 2004 IEEE Control System Technology Award for his contributions to the development of modeling and simulation techniques for multi-vehicle traffic networks. He led the development of traffic flow management software, Future ATM Concepts Evaluation Tool (FACET), which received the NASA Software of the Year Award in 2006 and the AIAA Engineering Software Award in 2009. He is a Fellow of the IEEE and the AIAA.