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Human-in-the-loop Learning and Control for Robot Teleoperation presents recent, research progress on teleoperation and robots, including human-robot interaction, learning and control for teleoperation with many extensions on intelligent learning techniques. The book integrates cutting-edge research on learning and control algorithms of robot teleoperation, neural motor learning control, wave variable enhancement, EMG-based teleoperation control, and other key aspects related to robot technology, presenting implementation tactics, adequate application examples and illustrative interpretations. Robots have been used in various industrial processes to reduce labor costs and improve work efficiency. However, most robots are only designed to work on repetitive and fixed tasks, leaving a gap with the human desired manufacturing effect. - Introduces research progress and technical contributions on teleoperation robots, including intelligent human-robot interactions and learning and control algorithms for teleoperation - Presents control strategies and learning algorithms to a teleoperation framework to enhance human-robot shared control, bi-directional perception and intelligence of the teleoperation system - Discusses several control and learning methods, describes the working implementation and shows how these methods can be applied to a specific and practical teleoperation system
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.
In the past years there has been considerable effort to move robots from industrial environments to our daily lives where they can collaborate and interact with humans to improve our life quality. One of the key challenges in this direction is to make a suitable robot control system that can adapt to humans and interactively learn from humans to facilitate the efficient and safe co-existence of the two. The applications of such robotic systems include: service robotics and physical human-robot collaboration, assistive and rehabilitation robotics, semi-autonomous cars, etc. To achieve the goal of integrating robotic systems into these applications, several important research directions must be explored. One such direction is the study of skill transfer, where a human operator’s skilled executions are used to obtain an autonomous controller. Another important direction is shared control, where a robotic controller and humans control the same body, tool, mechanism, car, etc. Shared control, in turn invokes very rich research questions such as co-adaptation between the human and the robot, where the two agents can benefit from each other’s skills or must adapt to each other’s behavior to achieve effective cooperative task executions. The aim of this Research Topic is to help bridge the gap between the state-of-the-art and above-mentioned goals through novel multidisciplinary approaches in human-in-the-loop robot control and learning.
This book presents the proceedings of the 32nd International Conference on Robotics in Alpe-Adria-Danube Region (RAAD), held in Bled, Slovenia, June 14-16, 2023. It gathers contributions by researchers from several countries on all major areas of robotic research, development and innovation, as well as new applications and current trends. The topics covered include: novel designs and applications of robotic systems, intelligent cooperating and service robots, advanced robot control, human-robot interfaces, robot vision systems, mobile robots, humanoid and walking robots, bio-inspired and swarm robotic systems, aerial, underwater and spatial robots, robots for ambient assisted living, medical robots and bionic prostheses, cognitive robots, cloud robotics, ethical and social issues in robotics, etc. Given its scope, the book offers a source of information and inspiration for researchers seeking to improve their work and gather new ideas for future developments.
The principal chapters of this book form a collection of technical articles sp- ning many areas of research in robotics, these are followed by a set of short r- iniscences and tributes written by former students of Professor George A. Bekey. Professor Bekey, a pioneer in robotics, retired from the University of Southern C- ifornia (USC) in 2002 after serving on its faculty for forty years. He maintains an association with USC as University Professor Emeritus. Professor Bekey turned 80 in June 2008 - this is his Festschrift. As one of Professor Bekey’s former students, it has been my privilege to know him for many years. This book represents the collective warm feelings of his former students, who remember their association with him in the fondest terms. Part I of this book is composed of technical chapters representing threads of active robotics research knitted loosely together. In many cases the themes of the chapters have their origins in the work the authors did when they were graduate students with Professor Bekey. These chapters are written for the reader interested in a sampling of modern research in Autonomous Robots. It is my hope that, for the serious reader, these chapters will serve as invitations to explore the ?eld via further reading and research.
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.
Over the next few decades, millions of people, with varying backgrounds and levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots will need to infer and predict humans’ intentions and internal objectives on the basis of past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics. This book introduces readers to robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures and other motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation, making it a valuable reference guide for graduate students with a basic knowledge of machine learning, and for researchers interested in wearable computing and robotic learning.
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.
For the things we have to learn before we can do them, we learn by doing them. Aristotle Teaching should be such that what is offered is perceived as a valuable gift and not as a hard duty. Albert Einstein The second most important job in the world, second only to being a good parent, is being a good teacher. S.G. Ellis The fast technological changes and the resulting shifts of market conditions require the development and use of educational methodologies and opportunities with moderate economic demands. Currently, there is an increasing number of edu- tional institutes that respond to this challenge through the creation and adoption of distance education programs in which the teachers and students are separated by physical distance. It has been verified in many cases that, with the proper methods and tools, teaching and learning at a distance can be as effective as traditional fa- to-face instruction. Today, distance education is primarily performed through the Internet, which is the biggest and most powerful computer network of the World, and the World Wide Web (WWW), which is an effective front-end to the Internet and allows the Internet users to uniformly access a large repertory of resources (text, data, images, sound, video, etc.) available on the Internet.