
Human-in-the-loop Learning and Control for Robot Teleoperation
Academic Press
Published on 13. April 2023
Book
Paperback/Softback
266 pages
978-0-323-95143-2 (ISBN)
Description
Human-in-the-loop Learning and Control for Robot Teleoperation presents recent, research progress on teleoperation and robots, including human-robot interaction, learning and control for teleoperation with many extensions on intelligent learning techniques. The book integrates cutting-edge research on learning and control algorithms of robot teleoperation, neural motor learning control, wave variable enhancement, EMG-based teleoperation control, and other key aspects related to robot technology, presenting implementation tactics, adequate application examples and illustrative interpretations.
Robots have been used in various industrial processes to reduce labor costs and improve work efficiency. However, most robots are only designed to work on repetitive and fixed tasks, leaving a gap with the human desired manufacturing effect.
Robots have been used in various industrial processes to reduce labor costs and improve work efficiency. However, most robots are only designed to work on repetitive and fixed tasks, leaving a gap with the human desired manufacturing effect.
More details
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Robot developers, automation-related researchers, postgraduate students and engineers in robotics, mechatronics, biomedical and control engineering
Product notice
Paperback (trade)
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 14 mm
Weight
364 gr
ISBN-13
978-0-323-95143-2 (9780323951432)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Chenguang Yang | Jing Luo | Ning Wang
Human-in-the-loop Learning and Control for Robot Teleoperation
E-Book
04/2023
Academic Press
€131.00
Available for download
Persons
Dr. Chenguang Yang is a Professor of Robotics with University of the West of England, and leader of Robot Teleoperation Group at the Bristol Robotics Laboratory. He received his Ph.D. degree in control engineering from the National University of Singapore in 2010, and postdoctoral training in human robotics from Imperial College London, U.K. His research interests lie in human-robot interaction and intelligent system design. Dr. Yang was awarded the EU Marie Curie International Incoming Fellowship, the U.K. EPSRC UKRI Innovation Fellowship, and the Best Paper Award of IEEE TRANSACTIONS ON ROBOTICS as well as over ten international conference best paper awards. He is a Co-Chair of the Technical Committee on Bio-Mechatronics and Bio-Robotics Systems, IEEE Systems, Man, and Cybernetics Society; and a Co-Chair of the Technical Committee on Collaborative Automation for Flexible Manufacturing, IEEE Robotics and Automation Society. He serves as an Associate Editor of a number of IEEE Transactions and other international leading journals. Dr. Jing Luo is currently an Associate Professor with Wuhan Institute of Technology. He received his Ph.D. degree in control science and engineering from the South China University of Technology in 2020. His research interests include robots control, teleoperation and human-robot interaction. Dr. Ning Wang is a Senior Lecturer of Robotics with the Bristol Robotics Laboratory, University of the West of England, United Kingdom. She received her M.Phil. and Ph.D. degrees in electronics engineering from the Department of Electronics Engineering, The Chinese University of Hong Kong, Hong Kong, in 2007 and 2011, respectively. Ning has rich project experience, she has been key member of EU FP7 Project ROBOT-ERA, EU Regional Development Funded Project ASTUTE 2020 and industrial projects with UK companies.
Author
Professor, Bristol Robotics Lab, UK
Associate Professor, Wuhan Institute of Technology, China
Senior Lecturer of Robotics, Bristol Robotics Laboratory, University of the West of England, UK
Content
1. Introduction
2. Software systems and platforms for teleoperation
3. Uncertainties compensation-based teleoperation control
4. User experience-enhanced teleoperation control
5. Shared control for teleoperation
6. Human-robot interaction in teleoperation systems
7. Task learning of teleoperation robot systems
2. Software systems and platforms for teleoperation
3. Uncertainties compensation-based teleoperation control
4. User experience-enhanced teleoperation control
5. Shared control for teleoperation
6. Human-robot interaction in teleoperation systems
7. Task learning of teleoperation robot systems