Prof. Jingtao Lei
Shanghai University, China
Biography: Jingtao Lei, received her Ph. D degree from the Beihang University in 2007, and as a postdoc at the Robotics Institute, Beihang University for two years. She joined the School of Mechantronic Engineering and Automation, Shanghai University in 2009. She has been a Professor of Mechatronic Engineering since Mar. 2018, and as a visiting scholar at The University of Sheffield, UK since Dec.2015 for one year. Her research directions include bionic robots, medical robots, rehabilitation robots and robot modular technology, etc. and has undertaken the national and ISO standards related to robotics.
Prof. Lei has led more than projects, including the National 863 Program, the National Natural Science Foundation of China, the National Key R&D Program of China, etc. She has published more than 80 papers, and more than 20 invention patents have been authorized. She won the second prize of Shanghai Technological Invention Award.
Speech Title：Bone Trauma Surgery Robot and Tissue Biomechanics
Abstract：Bone trauma surgery robot is one of the directions of orthopedic surgery robot. In this talk, I am going to introduce the research status of the reduction robot, including the operation mode, robot configuration and structural parameter optimization based on workspace analysis, reverse reconstruction and biomechanical analysis of skeletal muscle tissue.
Assoc. Prof. Chao Ma
University of Science and Technology Beijing, China
Biography: Dr.Chao Ma obtained the PhD in Control Science and Engineering from Harbin Institute of Technology in 2015. His current research interests include intelligent robotic systems, swarm intelligence systems and hybrid systems. He presided 1 National Natural Science Foundation of China and 2 Fundamental Research Funds for the Central Universities. He also participated in 2 key programs of National Natural Science Foundation of China. He has published over 20 SCI/EI papers.
Speech Title: Intelligent operation and skill learning of robots
Abstract: The dynamical tasks in the unstructured environment put forward higher requirements for the intelligence of robot operation. Robot operation based on autonomous learning technology can effectively improve the robustness and generalization of these tasks. This report focuses on the two research fields of autonomous reinforcement learning and human-machine cooperation, and discusses the advantages of using deep reinforcement learning from the perspective of human-machine hybrid intelligent fusion. Moreover, this report introduces the existing work of the reporter’s research group on the tasks of single robot operation, multi robot cooperative operation and human-robot cooperative operation, and finally analyzes the current technical challenges and makes prospects for its future research trend.
Dr. Zhan Li
Swansea University, UK
Biography: Dr. Zhan Li is a Senior Lecturer at the Department of Computer Science, Swansea University, U.K. He received his PhD degree from INRIA/University of Montpellier, France. Dr Zhan Li' main interests include AI, robotics, intelligent control and rehabilitation engineering. He is an Editorial Board Member of PLOS One, the Guest Editor of Frontiers in Neurorobotics, Frontiers in Neuroscience and Journal of Healthcare Engineering, and serves as IEEE RAS Technical Committee Member on Collaborative Automation for Flexible Manufacturing.
Dr. Wenbo Li
Tongji University, China
Biography: Dr. Wenbo Li is now a senior researcher scientist at School of Aerospace Engineering and Applied Mechanics, Institute for Advanced Study, Tongji University, Shanghai, China. He received the PhD degree in Mechanical Engineering from Shanghai Jiaotong University in 2019. After a 2.5-year postdoctoral research at the State Key Laboratory of Mechanical System and Vibration, Shanghai Jiaotong University, he joined Tongji University in 2022. He has published over 30 refereed papers in international journals such as Nature Communications, Soft Robotics, IEEE-ASME T MECH, etc. His current research interests include soft actuators and sensors, bioinspired soft robots, smart materials and structures.
Speech Title: High Speed and Agile Soft Mobile Robots
Abstract: Soft robots show excellent body compliance, adaptability, and mobility when cope with unstructured environments and human-robot interactions due to the softness of their constituent materials and structures. However, the intrinsic low stiffness and damping effect of the soft materials also limit their moving speed and efficiency which are far from conventional rigid robots. Most of the reported soft mobile robots have a low speed just as their bionic objects (slow moving mollusks like caterpillar, earthworm, etc.). In this talk, I am going to talk about our recently work on the dynamic actuation and control of two kinds of soft actuators (soft pneumatic actuators and soft electromagnetic actuators) and the development of high speed and agile soft mobile robots based on them.