Repetitive Motion Planning and Control of Redundant Robot Manipulators (eBook)

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Autor: Yunong Zhang

CHF 132.50

ISBN: 978-3-642-37518-7

Einband: PDF

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Repetitive Motion Planning and Control of Redundant Robot Manipulators presents four typical motion planning schemes based on optimization techniques, including the fundamental RMP scheme and its extensions. These schemes are unified as quadratic programs (QPs), which are solved by neural networks or numerical algorithms. The RMP schemes are demonstrated effectively by the simulation results based on various robotic models; the experiments applying the fundamental RMP scheme to a physical robot manipulator are also presented. As the schemes and the corresponding solvers presented in the book have solved the non-repetitive motion problems existing in redundant robot manipulators, it is of particular use in applying theoretical research based on the quadratic program for redundant robot manipulators in industrial situations. This book will be a valuable reference work for engineers, researchers, advanced undergraduate and graduate students in robotics fields.

Yunong Zhang is a professor at The School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China; Zhijun Zhang is a research fellow working at the same institute.

Autor	Zhang, Yunong / Zhang, Zhijun
Verlag	Springer Berlin Heidelberg
Einband	PDF
Erscheinungsjahr	2014
Seitenangabe	196 S.
Ausgabekennzeichen	Englisch
Abbildungen	XVII, 196 p.
Auflage	2013

Über den Autor Yunong Zhang

Yunong Zhang, PH.D., earned his B.S. degree from Huazhong University of Science and Technology, Wuhan, China, in 1996, his M.S. degree from South China University of Technology, Guangzhou, China, in 1999, and his Ph.D. from the Chinese University of Hong Kong, Shatin, Hong Kong, China, in 2003. He is currently a professor at the School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China. Dr. Zhang was supported by the Program for New Century Excellent Talents in Universities in 2007. He received the Best Paper Award from the International Symposium on Systems and Control in Aeronautics and Astronautics (ISSCAA) in 2008 and the Best Paper Award from the International Conference on Automation and Logistics (ICAL) in 2011. He was among the Highly Cited Scholars of China selected and published by Elsevier from 2014 to 2022.Jinjin Guo, Ph.D., earned her B.E. degree in measurement technology and instrument from Nanchang University, Nanchang, China, in 2016, her M.E. degree in control engineering from Sun Yat-sen University, Guangzhou, China, in 2018, and her Ph.D. in computer science and technology from Sun Yat-sen University, Guangzhou, China, in 2022. She is currently a lecturer at the School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China. Her main research interests include neural networks, numerical computation, and tracking control.