finelybook
Human-Robot Interaction Control Using Reinforcement Learning (IEEE Press Series on Systems Science and Engineering)
Part of: IEEE Press Series on Systems Science and Engineering (16 Books) | Author: Wen Yu and Adolfo Perrusquia
Publisher Finelybook 出版社: Wiley-IEEE Press; (October 19,2021)
Language 语言: English
pages 页数: 288 pages
ISBN-10 书号: 1119782740
ISBN-13 书号: 9781119782742
Book Description
A comprehensive exploration of the control schemes of human-robot interactions
In Human-Robot Interaction Control Using Reinforcement Learning,an expert team of authors delivers a concise overview of human-robot interaction control schemes and insightful presentations of novel,model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control and reinforcement learning before moving on to describe the typical environment model. The authors also describe some of the most famous identification techniques for parameter estimation.
Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical treatments and demonstrations that facilitate the understanding of control schemes and algorithms. It also describes stability and convergence analysis of human-robot interaction control and reinforcement learning based control.
The authors also discuss advanced and cutting-edge topics,like inverse and velocity kinematics solutions,H2 neural control,and likely upcoming developments in the field of robotics.
Readers will also enjoy:
A thorough introduction to model-based human-robot interaction control
Comprehensive explorations of model-free human-robot interaction control and human-in-the-loop control using Euler angles
Practical discussions of reinforcement learning for robot position and force control,as well as continuous time reinforcement learning for robot force control
In-depth examinations of robot control in worst-case uncertainty using reinforcement learning and the control of redundant robots using multi-agent reinforcement learning
Perfect for senior undergraduate and graduate students,academic researchers,and industrial practitioners studying and working in the fields of robotics,learning control systems,neural networks,and computational intelligence,Human-Robot Interaction Control Using Reinforcement Learning is also an indispensable resource for students and professionals studying reinforcement learning
