IROS 2020 - Plenaries

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IROS 2020 Distinguished Plenary Speakers

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	Speaker: Prof. Danica Kragic Title: Robotics and Artificial Intelligence Impacts on the Fashion Industry Abstract: This talk will overview how robotics and artificial intelligence can impact fashion industry. What can we do to make fashion industry more sustainable and what are the most difficult parts in this industry to automate? Concrete examples of research problems in terms of perception, manipulation of deformable materials and planning will be discussed in this context. Bio: Danica Kragic is a Professor at the School of Computer Science and Communication at the Royal Institute of Technology, KTH. She received MSc in Mechanical Engineering from the Technical University of Rijeka, Croatia in 1995 and PhD in Computer Science from KTH in 2001. She has been a visiting researcher at Columbia University, Johns Hopkins University and INRIA Rennes. She is the Director of the Centre for Autonomous Systems. Danica received the 2007 IEEE Robotics and Automation Society Early Academic Career Award. She is a member of the Royal Swedish Academy of Sciences, Royal Swedish Academy of Engineering Sciences and Young Academy of Sweden. She holds a Honorary Doctorate from the Lappeenranta University of Technology. Her research is in the area of robotics, computer vision and machine learning. She received ERC Starting and Advanced Grant. Her research is supported by the EU, Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research and Swedish Research Council. She is an IEEE Fellow.
	Speaker: Prof. Cynthia Breazeal Title: Living with Social Robots: from Research to Commercialization and Back. Abstract: Social robots are designed to interact with people in an interpersonal way, engaging and supporting collaborative social and emotive behavior for beneficial outcomes. We develop adaptive algorithmic capabilities and deploy multitudes of cloud-connected robots in schools, homes, and other living facilities to support long-term interpersonal engagement and personalization of specific interventions. We examine the impact of the robot’s social embodiment, emotive and relational attributes, and personalization capabilities on sustaining people's engagement, improving learning, impacting behavior, and shaping attitudes to help people achieve long-term goals. I will also highlight challenges and opportunities in commercializing social robot technologies for impact at scale. In a time where citizens are beginning to live with intelligent machines on a daily basis, we have the opportunity to explore, develop, study, and assess humanistic design principles to support and promote human flourishing at all ages and stages. Bio: Cynthia Breazeal is a Professor at the MIT Media Lab where she founded and Directs the Personal Robots Group. She is also Associate Director of the Media Lab in charge of new strategic initiatives, and she is spearheading MIT’s K-12 education initiative on AI in collaboration with the Media Lab, Open Learning and the Schwarzman College of Computing. She is recognized as a pioneer in the field of social robotics and human-robot interaction and is a AAAI Fellow. She is a recipient of awards by the National Academy of Engineering as well as the National Design Awards. She has received Technology Review’s TR100/35 Award and the George R. Stibitz Computer & Communications Pioneer Award. She has also been recognized as an award-winning entrepreneur, designer and innovator by CES, Fast Company, Entrepreneur Magazine, Forbes, and Core 77 to name a few. Her robots have been recognized by TIME magazine’s Best Inventions in 2008 and in 2017 where her award-wining Jibo robot was featured on the cover. She received her doctorate from MIT in Electrical Engineering and Computer Science in 2000.
	Speaker: Prof. Yukie Nagai Title: Cognitive Development in Humans and Robots: New Insights into Intelligence Abstract: Computational modeling of cognitive development has the potential to uncover the underlying mechanism of human intelligence as well as to design intelligent robots. We have been investigating whether a unified theory accounts for cognitive development and what computational framework embodies such a theory. This talk introduces a neuroscientific theory called predictive coding and shows how robots as well as humans acquire cognitive abilities using predictive processing neural networks. A key idea is that the brain works as a predictive machine; that is, the brain tries to minimize prediction errors by updating the internal model and/or by acting on the environment. Our robot experiments demonstrate that the process of minimizing prediction errors leads to continuous development from non-social to social cognitive abilities. Internal models acquired through their own sensorimotor experiences enable robots to interact with others by inferring their internal state. Our experiments inducing atypicality in predictive processing also explains why and how developmental disorders appear in social cognition. I discuss new insights into human and robot intelligence obtained from these studies. Bio: Yukie Nagai is a Project Professor at the International Research Center for Neurointelligence, the University of Tokyo. She received her Ph.D. in Engineering from Osaka University in 2004 and worked at the National Institute of Information and Communications Technology, Bielefeld University, and Osaka University. Since 2019, she leads Cognitive Developmental Robotics Lab at the University of Tokyo. Her research interests include cognitive developmental robotics, computational neuroscience, and assistive technologies for developmental disorders. Her research achievements have been widely reported in the media as novel techniques to understand and support human development. She also serves as the research director of JST CREST Cognitive Mirroring.

Speaker: Prof. Danica Kragic

Title: Robotics and Artificial Intelligence Impacts on the Fashion Industry

Abstract: This talk will overview how robotics and artificial intelligence can impact fashion industry. What can we do to make fashion industry more sustainable and what are the most difficult parts in this industry to automate? Concrete examples of research problems in terms of perception, manipulation of deformable materials and planning will be discussed in this context.

Bio: Danica Kragic is a Professor at the School of Computer Science and Communication at the Royal Institute of Technology, KTH. She received MSc in Mechanical Engineering from the Technical University of Rijeka, Croatia in 1995 and PhD in Computer Science from KTH in 2001. She has been a visiting researcher at Columbia University, Johns Hopkins University and INRIA Rennes. She is the Director of the Centre for Autonomous Systems. Danica received the 2007 IEEE Robotics and Automation Society Early Academic Career Award. She is a member of the Royal Swedish Academy of Sciences, Royal Swedish Academy of Engineering Sciences and Young Academy of Sweden. She holds a Honorary Doctorate from the Lappeenranta University of Technology. Her research is in the area of robotics, computer vision and machine learning. She received ERC Starting and Advanced Grant. Her research is supported by the EU, Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research and Swedish Research Council. She is an IEEE Fellow.

Speaker: Prof. Cynthia Breazeal

Title: Living with Social Robots: from Research to Commercialization and Back.

Abstract: Social robots are designed to interact with people in an interpersonal way, engaging and supporting collaborative social and emotive behavior for beneficial outcomes. We develop adaptive algorithmic capabilities and deploy multitudes of cloud-connected robots in schools, homes, and other living facilities to support long-term interpersonal engagement and personalization of specific interventions. We examine the impact of the robot’s social embodiment, emotive and relational attributes, and personalization capabilities on sustaining people's engagement, improving learning, impacting behavior, and shaping attitudes to help people achieve long-term goals. I will also highlight challenges and opportunities in commercializing social robot technologies for impact at scale. In a time where citizens are beginning to live with intelligent machines on a daily basis, we have the opportunity to explore, develop, study, and assess humanistic design principles to support and promote human flourishing at all ages and stages.

Bio: Cynthia Breazeal is a Professor at the MIT Media Lab where she founded and Directs the Personal Robots Group. She is also Associate Director of the Media Lab in charge of new strategic initiatives, and she is spearheading MIT’s K-12 education initiative on AI in collaboration with the Media Lab, Open Learning and the Schwarzman College of Computing. She is recognized as a pioneer in the field of social robotics and human-robot interaction and is a AAAI Fellow. She is a recipient of awards by the National Academy of Engineering as well as the National Design Awards. She has received Technology Review’s TR100/35 Award and the George R. Stibitz Computer & Communications Pioneer Award. She has also been recognized as an award-winning entrepreneur, designer and innovator by CES, Fast Company, Entrepreneur Magazine, Forbes, and Core 77 to name a few. Her robots have been recognized by TIME magazine’s Best Inventions in 2008 and in 2017 where her award-wining Jibo robot was featured on the cover. She received her doctorate from MIT in Electrical Engineering and Computer Science in 2000.

Speaker: Prof. Yukie Nagai

Title: Cognitive Development in Humans and Robots: New Insights into Intelligence

Abstract: Computational modeling of cognitive development has the potential to uncover the underlying mechanism of human intelligence as well as to design intelligent robots. We have been investigating whether a unified theory accounts for cognitive development and what computational framework embodies such a theory. This talk introduces a neuroscientific theory called predictive coding and shows how robots as well as humans acquire cognitive abilities using predictive processing neural networks. A key idea is that the brain works as a predictive machine; that is, the brain tries to minimize prediction errors by updating the internal model and/or by acting on the environment. Our robot experiments demonstrate that the process of minimizing prediction errors leads to continuous development from non-social to social cognitive abilities. Internal models acquired through their own sensorimotor experiences enable robots to interact with others by inferring their internal state. Our experiments inducing atypicality in predictive processing also explains why and how developmental disorders appear in social cognition. I discuss new insights into human and robot intelligence obtained from these studies.

Bio: Yukie Nagai is a Project Professor at the International Research Center for Neurointelligence, the University of Tokyo. She received her Ph.D. in Engineering from Osaka University in 2004 and worked at the National Institute of Information and Communications Technology, Bielefeld University, and Osaka University. Since 2019, she leads Cognitive Developmental Robotics Lab at the University of Tokyo. Her research interests include cognitive developmental robotics, computational neuroscience, and assistive technologies for developmental disorders. Her research achievements have been widely reported in the media as novel techniques to understand and support human development. She also serves as the research director of JST CREST Cognitive Mirroring.