Human-Robot Interaction Control Using Reinforcement Learning

Human-Robot Interaction Control Using Reinforcement Learning

Author: Wen Yu

Publisher: John Wiley & Sons

Published: 2021-10-19

Total Pages: 290

ISBN-13: 1119782740

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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.


Human-Robot Interaction Control Using Reinforcement Learning

Human-Robot Interaction Control Using Reinforcement Learning

Author: Wen Yu

Publisher: John Wiley & Sons

Published: 2021-10-06

Total Pages: 288

ISBN-13: 1119782767

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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.


Learning for Adaptive and Reactive Robot Control

Learning for Adaptive and Reactive Robot Control

Author: Aude Billard

Publisher: MIT Press

Published: 2022-02-08

Total Pages: 425

ISBN-13: 0262367017

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Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.


Computational Human-Robot Interaction

Computational Human-Robot Interaction

Author: Andrea Thomaz

Publisher:

Published: 2016-12-20

Total Pages: 140

ISBN-13: 9781680832082

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Computational Human-Robot Interaction provides the reader with a systematic overview of the field of Human-Robot Interaction over the past decade, with a focus on the computational frameworks, algorithms, techniques, and models currently used to enable robots to interact with humans.


Trends in Control and Decision-Making for Human–Robot Collaboration Systems

Trends in Control and Decision-Making for Human–Robot Collaboration Systems

Author: Yue Wang

Publisher: Springer

Published: 2017-01-24

Total Pages: 424

ISBN-13: 3319405330

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This book provides an overview of recent research developments in the automation and control of robotic systems that collaborate with humans. A measure of human collaboration being necessary for the optimal operation of any robotic system, the contributors exploit a broad selection of such systems to demonstrate the importance of the subject, particularly where the environment is prone to uncertainty or complexity. They show how such human strengths as high-level decision-making, flexibility, and dexterity can be combined with robotic precision, and ability to perform task repetitively or in a dangerous environment. The book focuses on quantitative methods and control design for guaranteed robot performance and balanced human experience from both physical human-robot interaction and social human-robot interaction. Its contributions develop and expand upon material presented at various international conferences. They are organized into three parts covering: one-human–one-robot collaboration; one-human–multiple-robot collaboration; and human–swarm collaboration. Individual topic areas include resource optimization (human and robotic), safety in collaboration, human trust in robot and decision-making when collaborating with robots, abstraction of swarm systems to make them suitable for human control, modeling and control of internal force interactions for collaborative manipulation, and the sharing of control between human and automated systems, etc. Control and decision-making algorithms feature prominently in the text, importantly within the context of human factors and the constraints they impose. Applications such as assistive technology, driverless vehicles, cooperative mobile robots, manufacturing robots and swarm robots are considered. Illustrative figures and tables are provided throughout the book. Researchers and students working in controls, and the interaction of humans and robots will learn new methods for human–robot collaboration from this book and will find the cutting edge of the subject described in depth.


Dynamics and Robust Control of Robot-Environment Interaction

Dynamics and Robust Control of Robot-Environment Interaction

Author: Miomir Vukobratovic

Publisher: World Scientific

Published: 2009

Total Pages: 657

ISBN-13: 9812834761

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This book covers the most attractive problem in robot control, dealing with the direct interaction between a robot and a dynamic environment, including the human-robot physical interaction. It provides comprehensive theoretical and experimental coverage of interaction control problems, starting from the mathematical modeling of robots interacting with complex dynamic environments, and proceeding to various concepts for interaction control design and implementation algorithms at different control layers. Focusing on the learning principle, it also shows the application of new and advanced learning algorithms for robotic contact tasks.


Robot Programming by Demonstration

Robot Programming by Demonstration

Author: Sylvain Calinon

Publisher: EPFL Press

Published: 2009-08-24

Total Pages: 248

ISBN-13: 9781439808672

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Recent advances in RbD have identified a number of key issues for ensuring a generic approach to the transfer of skills across various agents and contexts. This book focuses on the two generic questions of what to imitate and how to imitate and proposes active teaching methods.


Trust in Human-Robot Interaction

Trust in Human-Robot Interaction

Author: Chang S. Nam

Publisher: Academic Press

Published: 2020-11-17

Total Pages: 616

ISBN-13: 0128194731

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Trust in Human-Robot Interaction addresses the gamut of factors that influence trust of robotic systems. The book presents the theory, fundamentals, techniques and diverse applications of the behavioral, cognitive and neural mechanisms of trust in human-robot interaction, covering topics like individual differences, transparency, communication, physical design, privacy and ethics. - Presents a repository of the open questions and challenges in trust in HRI - Includes contributions from many disciplines participating in HRI research, including psychology, neuroscience, sociology, engineering and computer science - Examines human information processing as a foundation for understanding HRI - Details the methods and techniques used to test and quantify trust in HRI


Human-robot Interaction

Human-robot Interaction

Author: Michael A. Goodrich

Publisher: Now Publishers Inc

Published: 2007

Total Pages: 89

ISBN-13: 1601980922

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Presents a unified treatment of HRI-related issues, identifies key themes, and discusses challenge problems that are likely to shape the field in the near future. The survey includes research results from a cross section of the universities, government efforts, industry labs, and countries that contribute to HRI.


New Technologies, Development and Application III

New Technologies, Development and Application III

Author: Isak Karabegović

Publisher: Springer Nature

Published: 2020-05-04

Total Pages: 1021

ISBN-13: 3030468178

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This proceedings book features papers presented at the International Conference on New Technologies, Development and Application, held at the Academy of Sciences and Arts of Bosnia and Herzegovina in Sarajevo on 25th–27th June 2020. It covers a wide range of future technologies and technical disciplines, including complex systems such as Industry 4.0; patents in Industry 4.0; robotics; mechatronics systems; automation; manufacturing; cyber-physical and autonomous systems; sensors; networks; control; energy and renewable energy sources; automotive and biological systems; vehicular networking and connected vehicles; effectiveness and logistics systems; smart grids; nonlinear systems; power; social and economic systems; education; and IoT. The book focuses on the Fourth Industrial Revolution “Industry 4.0,” in which implementation will improve many aspects of human life in all segments and lead to changes in business paradigms and production models. Further, new business methods are emerging, transforming production systems, transport, delivery, and consumption, which need to be monitored and implemented by every company involved in the global market.