Adrià Colomé Carme Torras Colomé Reinforcement Learning of Bimanual Robot Skills

Reinforcement Learning of Bimanual Robot Skills

von Adrià Colomé Carme Torras

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Beschreibung

This book tackles all the stages and mechanisms involved in the learning of manipulation tasks by bimanual robots in unstructured settings, as it can be the task of folding clothes.

The first part describes how to build an integrated system, capable of properly handling the kinematics and dynamics of the robot along the learning process. It proposes practical enhancements to closed-loop inverse kinematics for redundant robots, a procedure to position the two arms to maximize workspace manipulability, and a dynamic model together with a disturbance observer to achieve compliant control and safe robot behavior.

In the second part, methods for robot motion learning based on movement primitives and direct policy search algorithms are presented. To improve sampling efficiency and accelerate learning without deteriorating solution quality, techniques for dimensionality reduction, for exploiting low-performing samples, and for contextualization and adaptability to changing situations are proposed.

In sum, the reader will find in this comprehensive exposition the relevant knowledge in different areas required to build a complete framework for model-free, compliant, coordinated robot motion learning.


This book tackles all the stages and mechanisms involved in the learning of manipulation tasks by bimanual robots in unstructured settings, as it can be the task of folding clothes.

The first part describes how to build an integrated system, capable of properly handling the kinematics and dynamics of the robot along the learning process. It proposes practical enhancements to closed-loop inverse kinematics for redundant robots, a procedure to position the two arms to maximize workspace manipulability, and a dynamic model together with a disturbance observer to achieve compliant control and safe robot behavior.

In the second part, methods for robot motion learning based on movement primitives and direct policy search algorithms are presented. To improve sampling efficiency and accelerate learning without deteriorating solution quality, techniques for dimensionality reduction, for exploiting low-performing samples, and for contextualization and adaptability to changingsituations are proposed.

In sum, the reader will find in this comprehensive exposition the relevant knowledge in different areas required to build a complete framework for model-free, compliant, coordinated robot motion learning.


Addresses the problems that arise when trying to learn bimanual robot motion tasks Presents an approach to learning complex robot tasks Discussess recent research related to kinematics, control, and learning

Autor*in

Adrià Colomé

Themen in »Reinforcement Learning of Bimanual Robot Skills«

Robotics Artificial Intelligence Reinforcement Learning Redundant Robots Robot Kinematics Robot Dynamics Robot Motion Characterization Dimensionality Reduction

Stimmen zu »Reinforcement Learning of Bimanual Robot Skills«

“Readers familiar with robotic manipulation will appreciate this work the most, as it is situated in the most recent journal articles and conference papers.” (Benjamin Wells, Computing Reviews, February 16, 2021)

“This book should be of interest to practicing and research engineers as well as Ph.D. students in the area of robotics and artificial intelligence in engineering practices and applications.” (Clementina Mladenova, zbMATH 1436.93001, 2020)


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Details

ISBN: 9783030263263
Verlag: Springer International Publishing
Erscheinung: 27.08.2019

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