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AI based robot safe learning and control

Zhou, Xuefeng.

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AI based robot safe learning and control

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	AI based robot safe learning and control/ by Xuefeng Zhou ... [et al.].
其他作者:	Zhou, Xuefeng.
出版者:	Singapore :Springer Singapore : : 2020.,
面頁冊數:	xvii, 127 p. :ill. (some col.), digital ;24 cm.
內容註:	Adaptive Jacobian based Trajectory Tracking for Redundant Manipulators with Model Uncertainties in Repetitive Tasks -- RNN based Trajectory Control for Manipulators with Uncertain Kinematic Parameters -- RNN Based Adaptive Compliance Control for Robots with Model Uncertainties -- Deep RNN based Obstacle Avoidance Control for Redundant Manipulators.
Contained By:	Springer eBooks
標題:	Robots - Control systems. -
電子資源:	https://doi.org/10.1007/978-981-15-5503-9
ISBN:	9789811555039

AI based robot safe learning and control
AI based robot safe learning and control[electronic resource] /by Xuefeng Zhou ... [et al.]. - Singapore :Springer Singapore :2020. - xvii, 127 p. :ill. (some col.), digital ;24 cm.

Adaptive Jacobian based Trajectory Tracking for Redundant Manipulators with Model Uncertainties in Repetitive Tasks -- RNN based Trajectory Control for Manipulators with Uncertain Kinematic Parameters -- RNN Based Adaptive Compliance Control for Robots with Model Uncertainties -- Deep RNN based Obstacle Avoidance Control for Redundant Manipulators.

Open access.

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.

ISBN: 9789811555039

Standard No.: 10.1007/978-981-15-5503-9doiSubjects--Topical Terms:

667305
Robots
--Control systems.

LC Class. No.: TJ211.35

Dewey Class. No.: 629.892

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506 $a Open access.
520 $a 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.
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