04494nam 22008535 450 991040422310332120230621160709.0981-15-5503-610.1007/978-981-15-5503-9(CKB)5280000000218447(DE-He213)978-981-15-5503-9(MiAaPQ)EBC6219799(Au-PeEL)EBL6219799(OCoLC)1159235503(oapen)https://directory.doabooks.org/handle/20.500.12854/32049(PPN)248594214(EXLCZ)99528000000021844720200602d2020 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierAI based Robot Safe Learning and Control /by Xuefeng Zhou, Zhihao Xu, Shuai Li, Hongmin Wu, Taobo Cheng, Xiaojing Lv1st ed. 2020.SingaporeSpringer Nature2020Singapore :Springer Singapore :Imprint: Springer,2020.1 online resource (XVII, 127 p. 42 illus., 35 illus. in color.)981-15-5502-8 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 .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.RoboticsAutomationControl engineeringArtificial intelligenceRobotics and Automationhttps://scigraph.springernature.com/ontologies/product-market-codes/T19020Control and Systems Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/T19010Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Robotics and AutomationControl and Systems TheoryArtificial IntelligenceRobotic EngineeringSafe ControlDeep Reinforcement LearningRecurrent Neural NetworkForce ControlObstacle OvoidanceAdaptive ControlTrajectory TrackingOpen AccessRoboticsAutomatic control engineeringArtificial intelligenceRobotics.Automation.Control engineering.Artificial intelligence.Robotics and Automation.Control and Systems Theory.Artificial Intelligence.629.892Zhou Xuefengauthttp://id.loc.gov/vocabulary/relators/aut845353Xu Zhihaoauthttp://id.loc.gov/vocabulary/relators/autLi Shuaiauthttp://id.loc.gov/vocabulary/relators/autWu Hongminauthttp://id.loc.gov/vocabulary/relators/autCheng Taoboauthttp://id.loc.gov/vocabulary/relators/autLv Xiaojingauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910404223103321AI based Robot Safe Learning and Control2034888UNINA