
Human-Robot Interaction Control Using Reinforcement Learning
Wiley-Blackwell (Publisher)
1st Edition
Published on 14. October 2021
Book
Hardback
260 pages
978-1-119-78274-2 (ISBN)
Description
This book gives brief overview of human-robot interaction control schemes, and presents novel model-free and reinforcement learning controllers. It begins with a brief introduction and state of art of human-robot interaction control and reinforcement learning. It then moves on to describe the typical environment model and some of the most famous identification techniques for parameters estimation. Later chapters address the robot-interaction schemes using impedance and admittance controllers, model-free controllers, and input forces/torques of the human operator. The authors also describe using the reinforcement learning approach for the position/force control task in discrete time, to achieve an optimal robot-environment interaction using a position/force control. They also explore how to design robust controllers based on the modified reinforcement learning under the worst-case uncertainty. Closing topics include inverse and velocity kinematics solution, H2 neural control, and future developments in the field.
More details
Series
Language
English
Place of publication
Hoboken
United States
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 20 mm
Weight
576 gr
ISBN-13
978-1-119-78274-2 (9781119782742)
Schweitzer Classification
Other editions
Additional editions

Wen Yu | Adolfo Perrusquia
Human-Robot Interaction Control Using Reinforcement Learning
E-Book
10/2021
1st Edition
Wiley
€122.99
Available for download

Wen Yu | Adolfo Perrusquia
Human-Robot Interaction Control Using Reinforcement Learning
E-Book
09/2021
1st Edition
Wiley
€118.99
Available for download
Persons
Author
Instituto Politecnico Nacional (CINVESTAV-IPN), Mexico City, Mexico
Cranfield University, Bedford, UK