Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

Xuefeng Zhou|Hongmin Wu|Juan Rojas|Zhihao Xu|Shuai Li

ISBN 10: 9811562628 / ISBN 13: 9789811562624

Edité par Springer Nature Singapore, 2020

A propos de cet article

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Is the first book on robot introspection based on nonparametric Bayesian methods in a data-driven&nbspcontext, which can be easily integrated into various robotic systemsIntroduces a fast, accurate, robot anomaly monitoring, diagnosis&nbspand&nb.

N° de réf. du vendeur 373577484

Détails bibliographiques

• Titre: Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
• Éditeur: Springer Nature Singapore
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 9811562628
• ISBN à 13 chiffres: 9789811562624
• Reliure: Gebunden
• État de l'article: New

A propos de ce titre

Synopsis

Introduction to Robot Introspection.- Nonparametric Bayesian Modeling of Multimodal Time Series.- Incremental Learning Robot Complex Task Representation and Identification.- Nonparametric Bayesian Method for Robot Anomaly Monitoring.- Nonparametric Bayesian Method for Robot Anomaly Diagnose.- Learning Policy for Robot Anomaly Recovery based on Robot.

À propos de l?auteur

Dr. Xuefeng Zhou is an Associate Professor and Leader of the Robotics Team at Guangdong Institute of Intelligent Manufacturing, Guangdong Academy of Science. He received his Ph.D. degree in Manufacturing and Automation from the South China University of Technology in 2011. His research mainly focuses on motion planning and control, force control and legged robots. He has published more than 40 journal articles and conference papers.

Dr. Hongmin Wu is a Researcher at Guangdong Institute of Intelligent Manufacturing, Guangdong Academy of Science. He received his Ph.D. degree in Mechanical Engineering from Guangdong University of Technology, Guangzhou, China, in 2019. His research mainly focuses on robot learning, autonomous manipulation, deep learning and human--robot collaboration. He has published more than 20 journal articles and conference papers.

Dr. Juan Rojas is an "100 Young Talents" Associate Professor at the Guangdong University of Technology inGuangzhou, China, where he works at the Biomimetics and Intelligent Robotics Lab (BIRL). Dr. Rojas currently researches robot introspection, human intention prediction, high-level state estimation and skill acquisition for manipulation tasks. He has published more than 40 journal articles and conference papers. Dr. Rojas serves as an Associate Editor of Advanced Robotic Journal since 2019 and Associate Editor of IEEE International Conference on Intelligent Robots and Systems (IROS) since 2017.

Dr. Zhihao Xu is a Researcher at Guangdong Institute of Intelligent Manufacturing, Guangdong Academy of Science. He received his Ph.D. degree in Control Science and Engineering from Nanjing University of Science and Technology, China, in 2016. His research mainly focuses on intelligent control theory, motion planning and control and force control. He has published more than 30 journal articles and conference papers.

Prof. Shuai Li is a Ph.D. Supervisor and Associate Professor (Reader) at the College of Engineering, Swansea University, UK. He received his Ph.D. degree in Electrical and Computer Engineering from Stevens Institute of Technology, New Jersey, USA, in 2014. His research interests are robot manipulation, automation and instrumentation, artificial intelligence and industrial robots. He has published over 80 papers in journals such as IEEE TAC, TII, TCYB, TIE and TNNLS. He serves as Editor-in-Chief of the International Journal of Robotics and Control and was the General Co-Chair of the 2018 International Conference on Advanced Robotics and Intelligent Control.