Advanced Teleoperation and Robot Learning for Dexterous Manipulation: 160

Advanced Teleoperation and Robot Learning for Dexterous Manipulation: 160 book cover

Advanced Teleoperation and Robot Learning for Dexterous Manipulation: 160

Author(s): Chenguang Yang (Author), Zhenyu Lu (Author), Ning Wang (Author)

  • Publisher: Springer
  • Publication Date: 12 April 2025
  • Language: English
  • Print length: 214 pages
  • ISBN-10: 3031785002
  • ISBN-13: 9783031785009

Book Description

This book offers an in-depth exploration of the interdisciplinary field of dexterous robotic manipulation, focusing on advanced methods that enable robots to autonomously learn, adapt, and perform a variety of tasks. It covers key topics such as teleoperation systems, advanced control frameworks, and bio-inspired autonomous learning. The book stands out by providing a comprehensive examination of both the technical and theoretical aspects of dexterous manipulation, with a particular emphasis on integrating advanced control and autonomous learning. The book is primarily aimed at researchers, engineers, and graduate students in the fields of robotics, artificial intelligence, and control systems. It is particularly useful for those interested in robotic manipulation, autonomous learning, and bio-inspired systems. The detailed technical explanations and cutting-edge research make it an essential resource for professionals seeking to push the boundaries of robotic dexterous manipulation. The book’s practical applications make it relevant for many real-world manipulation scenarios, including healthcare and manufacturing.

Editorial Reviews

From the Back Cover

This book offers an in-depth exploration of the interdisciplinary field of dexterous robotic manipulation, focusing on advanced methods that enable robots to autonomously learn, adapt, and perform a variety of tasks. It covers key topics such as teleoperation systems, advanced control frameworks, and bio-inspired autonomous learning. The book stands out by providing a comprehensive examination of both the technical and theoretical aspects of dexterous manipulation, with a particular emphasis on integrating advanced control and autonomous learning. The book is primarily aimed at researchers, engineers, and graduate students in the fields of robotics, artificial intelligence, and control systems. It is particularly useful for those interested in robotic manipulation, autonomous learning, and bio-inspired systems. The detailed technical explanations and cutting-edge research make it an essential resource for professionals seeking to push the boundaries of robotic dexterous manipulation. The book’s practical applications make it relevant for many real-world manipulation scenarios, including healthcare and manufacturing.

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