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AI based Robot Safe Learning and Control

by Xuefeng Zhou, Zhihao Xu, Shuai Li, Hongmin Wu, Taobo Cheng, Xiaojing Lv

AI based Robot Safe Learning and Control

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Book Description

This open book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors' papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.

This open book is licensed under a Creative Commons License (CC BY). You can download AI based Robot Safe Learning and Control ebook for free in PDF format (9.3 MB).

Table of Contents

Chapter 1
Adaptive Jacobian Based Trajectory Tracking for Redundant Manipulators with Model Uncertainties in Repetitive Tasks
Chapter 2
RNN Based Trajectory Control for Manipulators with Uncertain Kinematic Parameters
Chapter 3
RNN Based Adaptive Compliance Control for Robots with Model Uncertainties
Chapter 4
Deep RNN Based Obstacle Avoidance Control for Redundant Manipulators
Chapter 5
Optimization-Based Compliant Control for Manipulators Under Dynamic Obstacle Constraints
Chapter 6
RNN for Motion-Force Control of Redundant Manipulators with Optimal Joint Torque

Book Details

AI based Robot Safe Learning and Control
Engineering and Technology
ISBN13 Digital
ISBN10 Digital
PDF Size
9.3 MB

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