This book applies set-theoretic and reinforcement learning approaches to formulate, analyze, and solve the challenge of ensuring safe operation of robotic systems in an uncertain environment.
The authors adopt learning-supported set-theoretic methods -- specifically, the barrier Lyapunov function and the control barrier function -- to achieve desirable robust safety with guaranteed performance in continuous-time nonlinear control applications. They also combine reinforcement learning with control theory to ensure safe learning and optimization. The reinforcement learning-based optimization framework incorporates safety and robustness guarantees by applying theoretical analysis tools from the field of control.
This book will be of interest to researchers, engineers, and students specializing in robot planning and control.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Cong Li received the Ph.D. degree from the Chair of Automatic Control Engineering, Technical University of Munich, Germany in 2022. He was also a research associate at the Chair of Automatic Control Engineering, Technical University of Munich.
Yongchao Wang is at the Xi'an Research Institution of Hi-Technology, and a professor at the School of Aerospace Science and Technology, Xidian University, Xi'an, China. He was at the Chair of Automatic Control Engineering, Technical University of Munich, Germany.
Fangzhou Liu received the Doktor-Ingenieur degree in electrical engineering from the Technical University of Munich, Germany, in 2019. He was a lecturer and a research fellow at the Chair of Automatic Control Engineering, Technical University of Munich, Germany. He is now a full professor at the School of Astronautics, Harbin Institute of Technology, Harbin, China.
Xinglong Zhang received the B.S. degree from Zhejiang University, China, in 2011, the M.S. degree in mechanical engineering from the PLA University of Science and Technology, China, in 2014, and the Ph.D. degree in system and control from the Politecnico di Milano, Italy, 2018. He is currently an associate professor at the College of Intelligence Science and Technology, National University of Defense Technology, China.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. Assuring Safe Operation of Robotic Systems under Uncertainty: Control and Learning Methods applies set-theoretic and reinforcement learning approaches to formulate, analyze, and solve the challenge of ensuring safe operation of robotic systems in an uncertain environment.The authors adopt learning-supported, set-theoretic methodsspecifically, the barrier Lyapunov function and the control barrier functionto achieve desirable robust safety with guaranteed performance in continuous-time nonlinear control applications. They also combine reinforcement learning with control theory to ensure safe learning and optimization. The reinforcement learning-based optimization framework incorporates safety and robustness guarantees by applying theoretical analysis tools from the field of control.This book will be of interest to researchers, engineers, and students specializing in robot planning and control. This book applies set-theoretic and reinforcement learning approaches to formulate, analyze and solve the challenge of ensuring safe operation of robotic systems in an uncertain environment. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781041141204
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 50698197-n
Quantité disponible : 10 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 50698197
Quantité disponible : 10 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. N° de réf. du vendeur 409602607
Quantité disponible : 3 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 50698197-n
Quantité disponible : 10 disponible(s)
Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. 1st edition NO-PA16APR2015-KAP. N° de réf. du vendeur 26404600304
Quantité disponible : 3 disponible(s)
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Hardback. Etat : New. New copy - Usually dispatched within 4 working days. N° de réf. du vendeur B9781041141204
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 50698197
Quantité disponible : 10 disponible(s)
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9781041141204
Quantité disponible : Plus de 20 disponibles
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. Assuring Safe Operation of Robotic Systems under Uncertainty: Control and Learning Methods applies set-theoretic and reinforcement learning approaches to formulate, analyze, and solve the challenge of ensuring safe operation of robotic systems in an uncertain environment.The authors adopt learning-supported, set-theoretic methodsspecifically, the barrier Lyapunov function and the control barrier functionto achieve desirable robust safety with guaranteed performance in continuous-time nonlinear control applications. They also combine reinforcement learning with control theory to ensure safe learning and optimization. The reinforcement learning-based optimization framework incorporates safety and robustness guarantees by applying theoretical analysis tools from the field of control.This book will be of interest to researchers, engineers, and students specializing in robot planning and control. This book applies set-theoretic and reinforcement learning approaches to formulate, analyze and solve the challenge of ensuring safe operation of robotic systems in an uncertain environment. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781041141204
Quantité disponible : 1 disponible(s)