This book focusses on robotic skill learning and intelligent control for robotic manipulators including enabling of robots to efficiently learn motor and stiffness/force regulation policies from humans. It explains transfer of human limb impedance control strategies to the robots so that the adaptive impedance control for the robot can be realized.
This book focusses on robotic skill learning and intelligent control for robotic manipulators including enabling of robots to efficiently learn motor and stiffness/force regulation policies from humans. It explains transfer of human limb impedance control strategies to the robots so that the adaptive impedance control for the robot can be realized.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Chenguang Yang is a Co-Chair of the Technical Committee on Collaborative Automation for Flexible Manufacturing (CAFM), IEEE Robotics and Automation Society and Co-Chair of the Technical Committee on Bio-mechatronics and Bio-robotics Systems (B2S), IEEE Systems, Man, and Cybernetics Society. Chao Zeng is currently a Research Associate at the Institute of Technical Aspects of Multimodal Systems, Universität Hamburg. Jianwei Zhang is the director of TAMS, Department of Informatics, Universität Hamburg, Germany.
Inhaltsangabe
1. Introduction. 2. Robot platforms and software systems. 3. Human-robot stiffness transfer based on sEMG signals. 4. Learning and Generalisation of Variable Impedance Skills. 5. Learning human skills from multimodal demonstration. 6. Skill Modeling based on Extreme Learning Machine. 7. Neural Network Enhanced Robot Manipulator Control.
1. Introduction. 2. Robot platforms and software systems. 3. Human-robot stiffness transfer based on sEMG signals. 4. Learning and Generalisation of Variable Impedance Skills. 5. Learning human skills from multimodal demonstration. 6. Skill Modeling based on Extreme Learning Machine. 7. Neural Network Enhanced Robot Manipulator Control.
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