Advanced Teleoperation and Robot Learning for Dexterous Manipulation: 160 (Springer Tracts in Advanced Robotics, 160) - Hardcover

Yang, Chenguang; Lu, Zhenyu; Wang, Ning

Hardcover

ISBN 10: 3031785002 ISBN 13: 9783031785009

Publisher: Springer, 2025

Synopsis

This book offers an in-depth exploration of the interdisciplinary field of dexterous robotic manipulation, focusing on advanced methods that enable robots to autonomously learn, adapt, and perform a variety of tasks. It covers key topics such as teleoperation systems, advanced control frameworks, and bio-inspired autonomous learning. The book stands out by providing a comprehensive examination of both the technical and theoretical aspects of dexterous manipulation, with a particular emphasis on integrating advanced control and autonomous learning. The book is primarily aimed at researchers, engineers, and graduate students in the fields of robotics, artificial intelligence, and control systems. It is particularly useful for those interested in robotic manipulation, autonomous learning, and bio-inspired systems. The detailed technical explanations and cutting-edge research make it an essential resource for professionals seeking to push the boundaries of robotic dexterous manipulation. The book’s practical applications make it relevant for many real-world manipulation scenarios, including healthcare and manufacturing.

About this title

About the Author

Zhijun Li is an Associate Professor with the Department of Automation, Shanghai Jiaotong University. He received the Dr Eng Degree in mechatronics, Shanghai Jiao Tong University, PR China, in 2002. From 2003 to 2005, he was a postdoctoral fellow in the Department of Mechanical Engineering and Intelligent systems of The University of Electro-Communications, Tokyo, Japan. From 2005 to 2006, he was a research fellow in the Department of Electrical and Computer Engineering, National University of Singapore, and Nanyang Technological University, Singapore. Currently, he is an associate professor in the Department of Automation, Shanghai Jiao Tong University, PR China. Dr. Li is a senior member of the IEEE and his current research interests are adaptive/robust control, mobile manipulators, nonholonomic systems, etc. Chenguang Yang obtained the Bachelor's degree in Measurement and Control Instrument and Technology at the Northwestern Polytechnical University in 2001 and the PhD degree in Control Theory at the National University of Singapore in 2010. From 2005 to 2009, he was working  on adaptive/intelligent controllers for highly uncertain systems. In 2008, he worked for the TechX Challenge Urban Mobile Robot Competition organized by DSTA, Singapore, which is equivalent of the DARPA Grand Challenge in US. Together with teammates, he has developed a fully autonomous robot capable of climbing stairs, recognizing and operating an elevator, and navigating and searching for given targets in an unknown environment. From 2009 until 2010 he was with the Human Robotics Group in Imperial College London working on modeling of human neural-muscular control and development of robot control of human motor behavior. In connection with this he has developed a human-mimetic force- and impedance-adaptation algorithm for robots performing both stable and unstable tasks. Dr. Yang's current research interests are in the fields of intelligent robotic control, nonlinearcontrol and human-robot interaction. He is the author of more than twenty-five peer-reviewed journal and conference papers. He received Honorable Mention in the Mathematical Contest in Modeling (the US competition supported by supported by NSF and NSA), 2004. Since 2006, he has been serving as reviewer of a number of top journals such as the IEEE Transactions on Automatic Control, Automatica and the IEEE Transactions on Neural Networks. He is a member of the Technical Program Committee of the 2011 Chinese Control and Decision Conference (2011 CCDC) and of the IEEE. Liping Fan received his B.S.in the  Dept of Automation, Xiameng University in 1996, and from 2002, he is the founder of Shanghai Shengdisi Automation Equipment Co., LTD, and worked as CEO of the company until now, currently, he is the part-time graduate student of Dept of Auttomation, Shanghai Jiao Tong University. His research insterests are mechatronics system development, and control system design.

From the Back Cover

This book offers an in-depth exploration of the interdisciplinary field of dexterous robotic manipulation, focusing on advanced methods that enable robots to autonomously learn, adapt, and perform a variety of tasks. It covers key topics such as teleoperation systems, advanced control frameworks, and bio-inspired autonomous learning. The book stands out by providing a comprehensive examination of both the technical and theoretical aspects of dexterous manipulation, with a particular emphasis on integrating advanced control and autonomous learning. The book is primarily aimed at researchers, engineers, and graduate students in the fields of robotics, artificial intelligence, and control systems. It is particularly useful for those interested in robotic manipulation, autonomous learning, and bio-inspired systems. The detailed technical explanations and cutting-edge research make it an essential resource for professionals seeking to push the boundaries of robotic dexterous manipulation. The book’s practical applications make it relevant for many real-world manipulation scenarios, including healthcare and manufacturing.

Edition details

• Publisher: Springer
• Publication date: 2025
• Language: English
• ISBN 10: 3031785002
• ISBN 13: 9783031785009
• Binding: Hardcover
• Number of pages: 214