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dc.contributor.authorZhou, Xuefeng
dc.contributor.authorXu, Zhihao
dc.contributor.authorLi, Shuai
dc.contributor.authorWu, Hongmin
dc.contributor.authorCheng, Taobo
dc.contributor.authorLv, Xiaojing
dc.date.accessioned2021-02-10T13:55:42Z
dc.date.available2021-02-10T13:55:42Z
dc.date.issued2020
dc.identifierONIX_20200615_9789811555039_56
dc.identifier46200*
dc.identifierhttp://library.oapen.org/handle/20.500.12657/39583
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/32049
dc.description.abstractThis 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.
dc.languageEnglish
dc.rightsopen access
dc.subject.classificationbic Book Industry Communication::T Technology, engineering, agriculture::TJ Electronics & communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
dc.subject.classificationbic Book Industry Communication::T Technology, engineering, agriculture::TJ Electronics & communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence
dc.subject.otherRobotics and Automation
dc.subject.otherControl and Systems Theory
dc.subject.otherArtificial Intelligence
dc.subject.otherRobotic Engineering
dc.subject.otherSafe Control
dc.subject.otherDeep Reinforcement Learning
dc.subject.otherRecurrent Neural Network
dc.subject.otherForce Control
dc.subject.otherObstacle Ovoidance
dc.subject.otherAdaptive Control
dc.subject.otherTrajectory Tracking
dc.subject.otherOpen Access
dc.subject.otherRobotics
dc.subject.otherAutomatic control engineering
dc.subject.otherArtificial intelligence
dc.titleAI based Robot Safe Learning and Control
dc.typebook
oapen.identifier.doi10.1007/978-981-15-5503-9
oapen.relation.isPublishedBy9fa3421d-f917-4153-b9ab-fc337c396b5a
virtual.oapen_relation_isPublishedBy.publisher_nameSpringer Nature
virtual.oapen_relation_isPublishedBy.publisher_websitehttp://www.springernature.com/oabooks
oapen.imprintSpringer
oapen.pages127
oapen.place.publicationSingapore
dc.dateSubmitted2020-06-15T15:10:50Z


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Except where otherwise noted, this item's license is described as open access