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Advanced Teleoperation and Robot Learning for Dexterous Manipulation [Kõva köide]

  • Formaat: Hardback, 200 pages, kõrgus x laius: 235x155 mm, 105 Illustrations, color; 3 Illustrations, black and white; XIV, 200 p. 108 illus., 105 illus. in color., 1 Hardback
  • Sari: Springer Tracts in Advanced Robotics 160
  • Ilmumisaeg: 12-Apr-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031785002
  • ISBN-13: 9783031785009
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  • Kõva köide
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  • Formaat: Hardback, 200 pages, kõrgus x laius: 235x155 mm, 105 Illustrations, color; 3 Illustrations, black and white; XIV, 200 p. 108 illus., 105 illus. in color., 1 Hardback
  • Sari: Springer Tracts in Advanced Robotics 160
  • Ilmumisaeg: 12-Apr-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031785002
  • ISBN-13: 9783031785009
Teised raamatud teemal:

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.

Part I: Single-Leader-Dual-Follower Teleoperation for Cooperative
Manipulation.- Motion Regulation Solutions for Holding and Moving Objects in
Single-Leader-Dual-Follower Teleoperation.-  Single-Leader-Dual-Follower
Cooperative Manipulation of Deformable Objects.- Part II: Integrated
Autonomous Learning and Control Framework.-  A Small Opening Workspace
Control Strategy for Redundant Manipulator Based on Remote Center of Movement
Method.- Motor Learning and Generalization using Broad Learning Adaptive
Neural Control.- Hybrid Learning and Control using Improved Dynamical
Movement Primitive and Adaptive Neural Network Control.- Part III:
Bio-inspired Autonomous Learning for Dexterous Manipulations.- A  Constrained
DMP Framework for Robot Skills Learning and Generalization from Human
Demonstrations- Incremental Motor Skill Learning and Generalization From
Human Dynamic Reactions Based on Dynamic Movement Primitive and Fuzzy Logic
System.- Motor Learning and Generalization using Broad Learning Adaptive
Neural Control.