AI based Robot Safe Learning and Control

AI based Robot Safe Learning and Control Xuefeng Zhou Primary Author Zhihao Xu Primary Author Shuai Li Primary Author Hongmin Wu Primary Author Taobo Cheng Primary Author Xiaojing Lv Primary Author mixed material bibliography Springer Springer Nature 2020 en English 138 Halaman This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities. NONE 9789811555039 Perpustakaan UMA Online Public Access Catalog (OPAC) AI based Robot Safe Learning and Control 978-981-15-5503-9.jpg.jpg 23669 2026-08-21 10:26:05 2026-08-21 10:26:05 machine generated