TY  - GEN
AU  - Zhou,Xuefeng
AU  - Xu,Zhihao
AU  - Li,Shuai
AU  - Wu,Hongmin
AU  - Cheng,Taobo
AU  - Lv,Xiaojing
TI  - AI based Robot Safe Learning and Control
SN  - 978-981-15-5503-9
PY  - 2020///
CY  - Singapore
PB  - Springer Nature
KW  - Robotics
KW  - bicssc
KW  - Automatic control engineering
KW  - Artificial intelligence
KW  - Robotics and Automation
KW  - Control and Systems Theory
KW  - Artificial Intelligence
KW  - Robotic Engineering
KW  - Safe Control
KW  - Deep Reinforcement Learning
KW  - Recurrent Neural Network
KW  - Force Control
KW  - Obstacle Ovoidance
KW  - Adaptive Control
KW  - Trajectory Tracking
KW  - Open Access
N1  - Open Access
N2  - 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
UR  - https://library.oapen.org/bitstream/id/b24d731a-6dc8-4c23-82c9-eb92032e2a68/2020_Book_AIBasedRobotSafeLearningAndCon.pdf
UR  - http://library.oapen.org/handle/20.500.12657/39583
ER  -