"Our research tackles challenges in artificial intelligence known as 'Moravec's Paradox.' We aim to enhance robots' performance in various tasks, including those requiring multiple arms. We introduce a novel method, 'deep predictive learning,' which combines ideas from neuroscience's 'predictive coding' with robotics. This keynote presents our findings in robotics research utilizing deep predictive learning, along with our collaborations with prominent companies. We also provide an overview of our remarkable smart robot, 'AIREC,' backed by Japan's Moonshot project led by the Cabinet Office."
Tetsuya Ogata received the B.S., M.S., and D.E. degrees in mechanical engineering from Waseda University, Tokyo, Japan, in 1993, 1995, and 2000, respectively. He was a Research Associate with Waseda University from 1999 to 2001. From 2001 to 2003, he was a Research Scientist with the RIKEN Brain Science Institute, Saitama, Japan. From 2003 to 2012, he was an Associate Professor at the Graduate School of Informatics, Kyoto University, Kyoto, Japan. Since 2012, he has been a Professor with the Faculty of Science and Engineering, at Waseda University. From 2009 to 2015, he was a JST (Japan Science and Technology Agency) PREST Researcher. Since 2017, he is a Joint-appointed Fellow with the Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo. He served as director of the Robotics Society of Japan (RSJ) from 2014 to 2015 and of the Japanese Society of Artificial Intelligence (JSAI) from 2016 to 2018. He is currently a member of the director board of the Japan Deep Learning Association (JDLA) since 2017, and a director of the Institute of AI and Robotics, at Waseda University since 2020. His current research interests include deep learning for robot motion control, human–robot interaction, and dynamics of human–robot mutual adaptation.
Abstracts Assistive robots are designated to support people in their daily activities. In this keynote, I will discuss how such robots can deliver various types of assistance when designed as robot companions and what scientific questions are important to address in this context. My presentation will also introduce the UH Robot House, a unique facility for researching human-robot interaction, along with its robot residents. Robot House provides a realistic home environment off-campus where our research team can investigate the aforementioned questions looking towards a future where robotic companions play a greater role in caring for older people. The third part of the keynote will address one of the fundamental research questions of social robots, that is, how nonverbal communication can facilitate interactions between humans and robots. For that, I will present a few studies with human participants that look at what effects robot social behaviours have on human trust and acceptability towards them.Bio
Dr Patrick Holthaus researches social robotics and human-robot interaction, including a robot's nonverbal robot signalling, social credibility, and trust in assistive robots. He is further interested in interaction architectures and behaviour coordination as well as systems integration in heterogeneous environments. As manager of the Robot House, a unique facility for human-robot interaction, he brings together real-world applications and fundamental robotics research. Patrick is a member of the ACM and the IET and a Fellow of the Higher Education Academy. He is currently involved as a CoI of EPSRC Network+ project Tackling Frailty - Facilitating the Emergence of Healthcare Robots from Labs into Service (EMERGENCE) and an advisory board member of the Norwegian innovation project Human Interactive Robotics in Healthcare (HIRo). Previously, he has been a CoI of the UKRI TAS hub's pump priming project Kaspar explains and the AAIP-funded feasibility project Assuring safety and social credibility. He has been a postdoctoral researcher in the Robot House 2.0 project, an EPSRC strategic equipment grant and the Cognitive Service Robotics Apartment, a large-scale project within the DFG-funded excellence cluster CITEC where he was a member of the Cognitive Systems Engineering group. Dr Holthaus has received a PhD, MSc, and BSc degrees from Bielefeld University and a PGCert from the University of Hertfordshire.
Emotion measurement has become increasingly important in robotics-human interactions in recent years. Robots are increasingly used in many areas of everyday life, such as caregiving, education, entertainment, counseling, etc. In these applications, emotional interactions between humans and robots are key to success. In this talk, I will discuss the application of objective evaluation methods for human emotion measurement. Actual projects and research results on emotion measurement techniques using biometric signal processing will be presented. Through this talk, I will provide insights into the development of robotics technologies that incorporate emotion. It could lead to revolutionary advances in future robot applications.
Emi Yuda, she was born in Tokyo and now she is an associate professor at Tohoku University in Sendai, Japan. Her research are bio-signal processing and bio-medical big data analysis. She did her master degree at Tsukuba University and Dr.Eng at Niigata University. She was a research assistant at Santa Monica College (2013-2014), a NEDO project researcher at Nagoya City University (2015-2019), and an assistant professor at Tohoku University from (2019-2023).Senior Member of IEEE.
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