AI based robot safe learning and control / Xuefeng Zhou, Zhihao Xu, Shuai Li, Hongmin Wu, Taobo Cheng, Xiaojing Lv.
By: Zhou, Xuefeng [author.]
Contributor(s): Xu, Zhihao [author.] | Li, Shuai [author.] | Wu, Hongmin [author.] | Cheng, Taobo [author.] | Lv, Xiaojing [author.]
Language: English Publisher: Singapore : Springer, 2020Description: 1 online resource (xvii, 127 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9789811555022; 9789811555039; 9811555036Subject(s): Robots -- Control systems | Artificial intelligence | Artificial IntelligenceGenre/Form: Electronic books.DDC classification: LOC classification: TJ211.35Online resources: Full text is available at the Directory of Open Access Books. Click here to view. Summary: 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.| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|
EBOOK/OPEN ACCESS
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COLLEGE LIBRARY | COLLEGE LIBRARY | Not for loan |
Includes bibliographical references.
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.
Creative Commons Attribution 4.0 International CC BY 4.0
http://creativecommons.org/licenses/by/4.0/
Online resource; title from PDF title page (SpringerLink, viewed June 22, 2020).
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