Prof. Kenji Fujimoto
(Keynote Speaker)

Kyoto University, Japan

Keynote Lecture: Passivity based sliding mode control for electro-mechanical systems

Abstract: Both passivity based control and sliding mode control are well established useful techniques for nonlinear systems. Although they have been considered to be completely incompatible methods, there are actually some points of contact between them. This presentation shows recent results on their integration based on the port-Hamiltonian framework. Passivity based control is a method to find energy based Lyapunov function candidates for physical systems. It can generate Lyapunov functions for several objectives such as trajectory tracking control and/or those for output feedback control by a similar way to the standard artificial potential function method. On the other hand, sliding mode control is a technique to design a closed loop system with fast convergence by employing discontinuous high gain feedback without constructing any explicit Lyapunov function for the closed loop system. This presentation gives a brief summary on the author's developments on passivity based control with a recent attempt to integrate the two different techniques by employing a special class of non-smooth Lyapunov functions. This idea allows for highly flexible controller design that smoothly complements passivity based control and sliding mode control. Furthermore, it will also cover how the proposed framework is applied to electro-mechanical systems as well as conventional mechanical ones.

Biography: Kenji Fujimoto received his B.Sc. and M.Sc. degrees in Engineering and Ph.D. degree in Informatics from Kyoto University, Japan, in 1994, 1996 and 2001, respectively. He is currently a professor of Graduate School of Engineering, Kyoto University, Japan. From 1997 to 2004 he was a research associate of Graduate School of Engineering and Graduate School of Informatics, Kyoto University, Japan. From 2004 to 2012 he was an associate professor of Graduate School of Engineering, Nagoya University, Japan. From 1999 to 2000 he was a research fellow of Department of Electrical Engineering, Delft University of Technology, The Netherlands. He has held visiting research positions at the Australian National University, Australia and Delft University of Technology, The Netherlands, and RIKEN, Japan. He received The IFAC Congress Young Author Prize in IFAC World Congress 2005 and SICE Control Division Pioneer Award in 2007. He served as associate editors of IEEE Transactions on Automatic Control, IEEE CSS Conference Editorial Board, and SICE Journal of Measurement, Control, and System Integration. His research interests include nonlinear control and stochastic systems theory.

Prof. Zhengkun Yi
(Invited Speaker)

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China

Invited Lecture: Biomimetic Tactile Sensing: from Humans to Robots

Abstract: As robots move from laboratories to domestic environments, they will be required to perform manipulation tasks in unstructured environments. Such robots must be able to achieve sophisticated interactions with the environment and to perform complex tasks such as grasping objects with arbitrary unknown shapes. The sense of touch is a fundamental capability of robots to achieve these tasks. How to endow robots with human-like tactile abilities has attracted increasing attention in both academia and industry. In recent years, tactile sensors such as BioTac, GelSight, and TacTip have surpassed human tactile perception capabilities in terms of resolution, response speed, and measurement range, but there is still a big challenge to achieve human-like tactile sensation. One of the main difficulties is how to achieve precise understanding and efficient use of tactile signals. This talk will first introduce the human tactile perception and technologies of robotic tactile perception, and then cover the recent research progress including bionic tactile perception, sensor drift compensation, and robot tactile interaction based on artificial intelligence and brain-like intelligence methods.

Biography: Zhengkun Yi is currently a full professor in Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. He received the B.S. degree from University of Science and Technology of China (USTC) the M.E. degree from Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences and the Ph.D. degree from Nanyang Technological University (NTU) and Technische Universitaet Darmstadt (TUD). He was a postdoctoral fellow at Nanyang Technological University and National University of Singapore. His research interests include tactile sensing, robot learning, machine learning computer vision, etc. He has authored/co-authored more than 30 peer reviewed journal and conference papers, including IEEE-TIE, IEEE-TSMC, IEEE-TASE, etc. He received the NSFC excellent young scholar (overseas), the best student paper award in IEEE RCAR 2022. He is an associate editor for IEEE RAL and serves as publicity chair of IEEE RCAR 2021.