Author: Wen Yu
Publisher: John Wiley & Sons
ISBN: 1119782767
Category : Technology & Engineering
Languages : en
Pages : 288
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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.
Author: Takayuki Kanda
Publisher: CRC Press
ISBN: 1466506989
Category : Computers
Languages : en
Pages : 367
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Book Description
Human–Robot Interaction in Social Robotics explores important issues in designing a robot system that works with people in everyday environments. Edited by leading figures in the field of social robotics, it draws on contributions by researchers working on the Robovie project at the ATR Intelligent Robotics and Communication Laboratories, a world leader in humanoid interactive robotics. The book brings together, in one volume, technical and empirical research that was previously scattered throughout the literature. Taking a networked robot approach, the book examines how robots work in cooperation with ubiquitous sensors and people over telecommunication networks. It considers the use of social robots in daily life, grounding the work in field studies conducted at a school, train station, shopping mall, and science museum. Critical in the development of network robots, these usability studies allow researchers to discover real issues that need to be solved and to understand what kinds of services are possible. The book tackles key areas where development is needed, namely, in sensor networks for tracking humans and robots, humanoids that can work in everyday environments, and functions for interacting with people. It introduces a sensor network developed by the authors and discusses innovations in the Robovie humanoid, including several interactive behaviors and design policies. Exploring how humans interact with robots in daily life settings, this book offers valuable insight into how robots may be used in the future. The combination of engineering, empirical, and field studies provides readers with rich information to guide in developing practical interactive robots.
Author: Aude Billard
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425
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Book Description
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.
Author: Wen Yu
Publisher: John Wiley & Sons
ISBN: 1119782740
Category : Technology & Engineering
Languages : en
Pages : 290
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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.
Author: Andrea Thomaz
Publisher:
ISBN: 9781680832082
Category : Technology & Engineering
Languages : en
Pages : 140
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Book Description
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.
Author: Yue Wang
Publisher: Springer
ISBN: 3319405330
Category : Technology & Engineering
Languages : en
Pages : 424
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Book Description
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.
Author: Chang S. Nam
Publisher: Academic Press
ISBN: 0128194731
Category : Psychology
Languages : en
Pages : 616
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Book Description
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
Author: Miomir Vukobratovic
Publisher: World Scientific
ISBN: 9812834761
Category : Technology & Engineering
Languages : en
Pages : 657
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Book Description
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.
Author: Sylvain Calinon
Publisher: EPFL Press
ISBN: 9781439808672
Category : Computers
Languages : en
Pages : 248
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Book Description
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.
Author: Isak Karabegović
Publisher: Springer Nature
ISBN: 3030468178
Category : Technology & Engineering
Languages : en
Pages : 1021
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Book Description
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.
