Electronic Resource

AI based Robot Safe Learning and Control

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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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Detail Information

Series Title

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Call Number

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Publisher

Singapore : Springer Nature., 2020

Collation

127 hlm; ill., lamp.,

Language

English

ISBN/ISSN

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Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

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Specific Detail Info

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Statement of Responsibility

Zhou, Xuefeng Xu, Zhihao Li, Shuai Wu, Hongmin Cheng, Taobo Lv, Xiaojing

Other Information

Cataloger

ida

Source

https://directory.doabooks.org/handle/20.500.12854/32049

Validator

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Digital Object Identifier (DOI)

10.1007/978-981-15-5503-9

Journal Volume

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Journal Issue

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Subtitle

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Parallel Title

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