Plenary Speaker

Prof. Gentiane Venture

AIST Fellow
University of Tokyo, Japan

Biography: Gentiane Venture is a French Roboticist working in academia in Tokyo. She is a professor with the University of Tokyo and a cross appointed fellow with AIST. She obtained her MSc and PhD from Ecole Centrale/University of Nantes in 2000 and 2003 respectively. She worked at CEA in 2004 and for 6 years at the University of Tokyo. In 2009 she started with Tokyo University of Agriculture and Technology where she has established an international research group working on human science and robotics, before moving to her present affiliation in 2022. With her group she conducts theoretical and applied research on motion dynamics, robot control and non-verbal communication to study the meaning of living with robots. Her work is highly interdisciplinary, collaborating with therapists, psychologists, neuroscientists, sociologists, philosophers, ergonomists, artists and designers.

Working with expressive machines

Abstract:During physical Human-Robot Interaction human and robot take action together to fulfill a goal or a task. However, the way to achieve this goal may vary depending on their point of view. This is particularly the case if they do not have access to the same information or knowledge. This talk aims at presenting some directions to address the challenges that arise when a robot uses non-verbal communication to communicate with the human during a physical HRI. How is it possible to understand a possible conflict arising in the interaction and how is it possible to address it from the perceptual and control point of view? In this presentation I will give hints to answer these questions through our work in pHRI.



Prof. Sardar M. N. Islam

Victoria University, Australia

Biography: Professor Dr. Sardar M. N. Islam (Naz) is Professior from Victoria University, Australia. He adopts a global and humanistic approach in his research and academic works. His academic work has gained international acclaim, resulting in many (1) Honours and Awards, (1) distinguished visiting or adjunct professorial appointments in different countries, (2) appointments in editorial roles of journals, and (3) keynote speeches at international conferences in several countries. He has published 31 scholarly authored academic books in different disciplines. Each of these books makes significant scientific contributions to the literature. These books are published by prestigious publishers and the majority of books are published in highly regarded book series. He has also published about 250 articles, including some top leading international journal articles in his specialised research areas.

Artificial intelligence, automation, and robotics:
Game theory mathematics, Python programming, and applications in emerging technologies

Abstract:We are living in a science fiction world where artificial intelligence is deterring the future of the world and mankind. Many things are being automated because of artificial intelligence. Robots are being created by artificial intelligence to automate many things in he world. Many real life environments are characterized by the existence of intelligent multiagent systems where intelligent agents or robots interact, formulate strategies, cooperate, coordinate, design systems, and plan actions autonomously for achieving their goals. Game theory analyses, formulates strategies and designs rules or mechanisms for robots in these multiagent systems on the basis of artificial intelligence. For specifying, characterising and modelling and designing these intelligent multiagent systems, mathematical game theory models of different forms can be developed such as static, dynamic, evolutionary, differential, and stochastic game theory models. Different algorithms such as Nash equilibrium, joint optimization, evolutionary algorithms, neural networks, genetic algorithms, and other machine learning algorithms can be applied to different game theory models for analysing, solving, and computing these models. Computer programs such as Python can be used for computing and implementing these models and AI algorithms. Findings from these models are used to formulate strategies, cooperate, coordinate, design systems, and plan actions by different intelligent agents in different disciplines in engineering, business, computer science, etc. Robotics based on game theory and artificial intelligence has applications in different emerging technologies in engineering, business, computer science, etc. It is an important area for doing highly useful academic and practical activities and for academics and practitioners for building their careers. Therefore, it is necessary to give priority to this area for research and development in emerging technologies in different disciplines in engineering, business, computer science, etc.



Prof. Ding Wang

Beijing University of Technology, China

Biography: Ding Wang received the Ph.D. degree in control theory and control engineering from Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 2012. He was an Associate Professor with The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. He is currently a Full Professor with the Faculty of Information Technology, Beijing University of Technology. He has authored or co-authored over 120 journal and conference papers and four monographs. His current research interests include adaptive critic control with industrial applications, reinforcement learning, and intelligent systems. Dr. Wang was successively selected as a Clarivate Highly Cited Researcher in 2020 and 2021. He is a member of IEEE/CAA Journal of Automatica Sinica Early Career Advisory Board. He currently or formerly serves as an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Neural Networks, International Journal of Robust and Nonlinear Control, International Journal of Adaptive Control and Signal Processing, Neurocomputing, and Acta Automatica Sinica.

Event-based intelligent critic control for complex nonlinear systems

Abstract:With the rapid development of intelligent control, adaptive critic learning is regarded as a promising scheme to accomplish intelligent optimization by introducing the evaluation component. Due to the increasing scale of complex nonlinear systems, the communication burden problem is becoming more and more serious. Therefore, it is extremely necessary to establish advanced and effective event-based critic learning schemes for reducing computational burden. First, for a class of complex discrete-time nonlinear systems, a reasonable triggering condition is designed under the iterative critic learning framework to improve the utilization efficiency of resources and ensure that the closed-loop system has an excellent control performance. The optimal tracking control problem can be further studied by constructing an augmented plant. Second, the disturbance is introduced into the controlled system, which establishes a dual event-triggered control scheme. Two separate triggering conditions are given to trigger and update the control input and the disturbance asynchronously. The interference between them is avoided and the independence of the control input and the disturbance is guaranteed. For overcoming the challenge caused by the actuator saturation, the control input is constrained to a bounded range. Next, in order to expand the developed dual event-triggered control scheme, an event-based adaptive critic algorithm with multiple triggering conditions is investigated to address multi-player nonzero-sum game problems. According to the setting triggering conditions, we prove that the real cost function possesses a predetermined upper bound, which realizes the cost guarantee of the controlled system. Finally, the stability of the controlled system is proved from multiple perspectives by constructing appropriate Lyapunov functions. The developed algorithms are also applied to some nonlinear systems including the wastewater treatment plant.