Prof. Clément Gosselin (IEEE Fellow, ASME Fellow)
Department of Mechanical Engineering
Québec, Qc, Canada
BIO: Clément Gosselin received the Ph.D. degree from McGill University in Canada and completed a post-doctoral fellowship at INRIA in France. Since 1989, he has been with the Department of Mechanical Engineering at Université Laval, Québec, Canada where he is a Full Professor since 1997 and where has held a Canada Research Chair from 2001 to 2021. His research interests are kinematics, dynamics and control of robotic mechanical systems with a particular emphasis on the mechanics of grasping, the kinematics and dynamics of parallel manipulators, the development of human-friendly robots and the synthesis of haptic devices. He is an Editor of the IEEE Robotics and Automation Letters and an Associate Editor of the ASME Journal of Mechanisms and Robotics. Dr. Gosselin received several awards including the ASME DED Mechanisms and Robotics Committee Award in 2008, the ASME Machine Design Award in 2013 and the IFToMM Award of Merit in 2019. He was appointed Officer of the Order of Canada in 2010 for contributions to research in parallel mechanisms and underactuated systems. He is a fellow of the ASME, of the IEEE and of the Royal Society of Canada.
Speech Title: Human-Robot Haptic Interaction: a Handshaking Anthropomorphic Robotic Interface
Abstract: This presentation discusses the haptic interaction between humans and robots in natural settings. The paradigm is exemplified by a novel haptic interface developed for an advanced human-robot interaction. The objective of the proposed robotic system is to reproduce one of the most common greetings between people, i.e., the handshake. The design process of the robotic mechanism is first discussed, pointing out the force and velocity requirements that are established in order to obtain a realistic handshake. The mechanical design of the prototype of the robot hand is then described and illustrated. A working prototype, mainly built using 3D printing, is presented. Then, the development and implementation of a control law that allows the device to properly respond to external stimuli or, in other words, to provide a desirable haptic rendering is presented. The experimental validation of the prototype, including the performance of human-robot handshaking using a 7-dof serial robot, is also described and discussed.
Prof. Gang Feng (IEEE Fellow)
Chair Professor of Mechatronic Engineering
Director of Centre for Robotics and Automation
City University of Hong Kong
BIO: Gang Feng received the B.Eng and M.Eng. Degrees in Automatic Control from Nanjing Aeronautical Institute, China in 1982 and in 1984 respectively, and the Ph.D. degree in Electrical Engineering from the University of Melbourne, Australia in 1992.
Professor Feng was a Lecturer in Royal Melbourne Institute of Technology, 1991 and a Senior Lecturer/Lecturer, University of New South Wales, 1992-1999. He has been with City University of Hong Kong (CityU) since 2000, where he is now a Chair Professor of Mechatronic Engineering. He has received Alexander von Humboldt fellowship, the IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award, the outstanding research award and President award of CityU, and several best conference paper awards. He is listed as a SCI highly cited researcher by Clarivate Analytics since 2016. His research interests include intelligent systems and control, networked control systems, and multi-agent systems and control.
Professor Feng is a fellow of IEEE. He has been the Associate Editor of IEEE Trans. Automatic Control, IEEE Trans. on Fuzzy Systems, IEEE Trans. Systems, Man, & Cybernetics, Mechatronics, Journal of Systems Science & Complexity, Journal of Guidance, Navigation & Control, and Journal of Control Theory and Applications. He is also on the advisory board of Unmanned Systems.
Speech Title: Robust Cooperative Output Regulation of Heterogeneous Uncertain Linear Multi-Agent Systems with Unbounded Transmission Delays
Abstract: This talk presents our recent work on robust cooperative output regulation of heterogeneous uncertain linear multi-agent systems under unbounded distributed transmission delays. A novel distributed observer is first proposed to estimate the state of an exosystem in the presence of unbounded distributed transmission delays. Then two novel distributed controllers, one based on state feedback and the other based on output feedback, are further developed without any prior knowledge of the unbounded transmission delays. It is shown that the resulting closed loop multi-agent systems can achieve robust cooperative output regulation. It is also shown that better transient performance is achieved with our proposed controllers in contrast to many existing low gain controllers which are proposed to deal with both bounded and unbounded transmission delays. Our results can be directly applied to solve cooperative output regulation problems of multi-agent systems with bounded distributed or constant transmission delays. Furthermore, our results can also be directly applied to solve leader-following consensus problems of multi-agent systems with unbounded distributed, bounded distributed or constant transmission delays. Finally, a simulation example is provided to illustrate the effectiveness of the proposed controllers.
Prof. Danwei WANG (IEEE Fellow)
Nanyang Technological University, Singapore
BIO: WANG Danwei is Fellow, Academy of Engineering Singapore, Fellow of IEEE, Fellow, AvH (Germany) and recipient of the First-Class Award of Shanghai Science and Technology. He received his Ph.D degree from the University of Michigan, Ann Arbor, USA. Currently, he is professor, School of Electrical and Electronic Engineering, NTU, He is Editor, IEEE IROS (International Conference on Intelligent Robotics and Systems) since 2019. He has published 6 books, 7 book chapters, 9 patents and over 500 technical papers and articles in international refereed journals and conferences. SCI citations to his papers amount 8800+ as of Feb 2023 and Google Scholar citations are well over 17,000. He also set up a spin-off company to commercialise his research results in the area of sensing systems and autonomous systems.
Speech Title: Robust Perception for Intelligent Systems
Abstract: Perception is a key module to any intelligent systems which operate in outdoor environment. The perception must be robust and consistent in all adverse weather conditions. Outdoor applications and industries require intelligent and autonomous systems to work continuously under changing lighting and weather conditions. Robust perception capability enables the decision making and execution at various levels and loops of a complex intelligent autonomous systems. This talk presents some achievements with common sensors, such as LiDAR and cameras, as well as multi-modal sensing and perception for reliable and robust outdoor scenarios. The combination of different sensors will lead to 3D digital twin, seamless wide FOV video streams and robust perception in complex outdoor natural environment and adverse weather conditions.
Prof. Emily Cross
ETH Zürich, Switzerland
BIO: A cognitive neuroscientist by training, Emily arrived at ETH Zurich in the spring of 2023, where she leads the Social Brain Sciences Professorship and co-directs the Social Brain in Action Laboratory. Prior to this, she has held professorships at Bangor University (Wales), University of Glasgow (Scotland), Macquarie University (Australia) and the MARCS Institute at Western Sydney University (Australia). The defining characteristic of the work conducted by Cross and her research team is a focus on how different kinds of embodied experience shape how we learn from and perceive others in a complex social world, and across a variety of experience domains. Throughout her career, Cross has combined intensive learning paradigms with pre-/post-training brain imaging measures, to build a richer understanding of experience-dependent plasticity at brain and behavioural levels. She is especially well-regarded for developing innovative neurocognitive paradigms to explore the mechanisms and consequences of people’s social engagement with robots.