Learning For Adaptive And Reactive Robot Control
DOWNLOAD
Download Learning For Adaptive And Reactive Robot Control PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Learning For Adaptive And Reactive Robot Control book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Learning For Adaptive And Reactive Robot Control
DOWNLOAD
Author : Aude Billard
language : en
Publisher: MIT Press
Release Date : 2022-02-08
Learning For Adaptive And Reactive Robot Control written by Aude Billard and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-08 with Technology & Engineering categories.
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.
Adaptive Control For Robotic Manipulators
DOWNLOAD
Author : Dan Zhang
language : en
Publisher: CRC Press
Release Date : 2017-02-03
Adaptive Control For Robotic Manipulators written by Dan Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-03 with Science categories.
The robotic mechanism and its controller make a complete system. As the robotic mechanism is reconfigured, the control system has to be adapted accordingly. The need for the reconfiguration usually arises from the changing functional requirements. This book will focus on the adaptive control of robotic manipulators to address the changed conditions. The aim of the book is to summarise and introduce the state-of-the-art technologies in the field of adaptive control of robotic manipulators in order to improve the methodologies on the adaptive control of robotic manipulators. Advances made in the past decades are described in the book, including adaptive control theories and design, and application of adaptive control to robotic manipulators.
Human In The Loop Robot Control And Learning
DOWNLOAD
Author : Luka Peternel
language : en
Publisher: Frontiers Media SA
Release Date : 2020-01-22
Human In The Loop Robot Control And Learning written by Luka Peternel and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-22 with categories.
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.
New Developments And Advances In Robot Control
DOWNLOAD
Author : Nabil Derbel
language : en
Publisher: Springer
Release Date : 2019-01-24
New Developments And Advances In Robot Control written by Nabil Derbel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-24 with Technology & Engineering categories.
This book highlights relevant studies and applications in the area of robotics, which reflect the latest research, from interdisciplinary theoretical studies and computational algorithm development, to representative applications. It presents chapters on advanced control, such as fuzzy, neural, backstepping, sliding mode, adaptive, predictive, diagnosis and fault tolerant control etc. and addresses topics including cloud robotics, cable-driven robots, two-wheeled robots, mobile robots, swarm robots, hybrid vehicle, and drones. Each chapter employs a uniform structure: background, motivation, quantitative development (equations), case studies/illustration/tutorial (simulations, experiences, curves, tables, etc.), allowing readers to easily tailor the techniques to their own applications.
Adaptive Neural Network Control Of Robotic Manipulators
DOWNLOAD
Author : Tong Heng Lee
language : en
Publisher: World Scientific
Release Date : 1998
Adaptive Neural Network Control Of Robotic Manipulators written by Tong Heng Lee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Introduction; Mathematical background; Dynamic modelling of robots; Structured network modelling of robots; Adaptive neural network control of robots; Neural network model reference adaptive control; Flexible joint robots; task space and force control; Bibliography; Computer simulation; Simulation software in C.
Ai Based Robot Safe Learning And Control
DOWNLOAD
Author : Xuefeng Zhou
language : en
Publisher: Springer
Release Date : 2020-07-08
Ai Based Robot Safe Learning And Control written by Xuefeng Zhou and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-08 with Technology & Engineering categories.
This open access 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.
Learning Control
DOWNLOAD
Author : Dan Zhang
language : en
Publisher: Elsevier
Release Date : 2020-12-05
Learning Control written by Dan Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-05 with Technology & Engineering categories.
Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also introducing exciting cutting-edge technologies in the field of learning-based control. State-of-the-art techniques involving machine learning and artificial intelligence (AI) are covered, as are foundational control theories and more established techniques such as adaptive learning control, reinforcement learning control, impedance control, and deep reinforcement control. Each chapter includes case studies and real-world applications in robotics, AI, aircraft and other vehicles and complex dynamical systems. Computational methods for control systems, particularly those used for developing AI and other machine learning techniques, are also discussed at length. Provides foundational control theory concepts, along with advanced techniques and the latest advances in adaptive control and robotics Introduces state-of-the-art learning-based control technologies and their applications in robotics and other complex dynamical systems Demonstrates computational techniques for control systems Covers iterative learning impedance control in both human-robot interaction and collaborative robots
Ai Based Robot Safe Learning And Control
DOWNLOAD
Author : Xuefeng Zhou
language : en
Publisher:
Release Date : 2020-10-09
Ai Based Robot Safe Learning And Control written by Xuefeng Zhou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-09 with Computers categories.
This open access 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 work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Robot Learning Human Skills And Intelligent Control Design
DOWNLOAD
Author : Chenguang Yang
language : en
Publisher: CRC Press
Release Date : 2021-06-21
Robot Learning Human Skills And Intelligent Control Design written by Chenguang Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-21 with Computers categories.
In the last decades robots are expected to be of increasing intelligence to deal with a large range of tasks. Especially, robots are supposed to be able to learn manipulation skills from humans. To this end, a number of learning algorithms and techniques have been developed and successfully implemented for various robotic tasks. Among these methods, learning from demonstrations (LfD) enables robots to effectively and efficiently acquire skills by learning from human demonstrators, such that a robot can be quickly programmed to perform a new task. This book introduces recent results on the development of advanced LfD-based learning and control approaches to improve the robot dexterous manipulation. First, there's an introduction to the simulation tools and robot platforms used in the authors' research. In order to enable a robot learning of human-like adaptive skills, the book explains how to transfer a human user’s arm variable stiffness to the robot, based on the online estimation from the muscle electromyography (EMG). Next, the motion and impedance profiles can be both modelled by dynamical movement primitives such that both of them can be planned and generalized for new tasks. Furthermore, the book introduces how to learn the correlation between signals collected from demonstration, i.e., motion trajectory, stiffness profile estimated from EMG and interaction force, using statistical models such as hidden semi-Markov model and Gaussian Mixture Regression. Several widely used human-robot interaction interfaces (such as motion capture-based teleoperation) are presented, which allow a human user to interact with a robot and transfer movements to it in both simulation and real-word environments. Finally, improved performance of robot manipulation resulted from neural network enhanced control strategies is presented. A large number of examples of simulation and experiments of daily life tasks are included in this book to facilitate better understanding of the readers.
Control And Learning In Robotic Systems
DOWNLOAD
Author : John X. Liu
language : en
Publisher:
Release Date : 2005
Control And Learning In Robotic Systems written by John X. Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Technology & Engineering categories.
Robotics began as a science fiction creation which has become quite real, first in assembly line operations such as automobile manufacturing, aeroplane construction etc. They have now reached such areas as the internet, ever-multiplying-medical uses and sophisticated military applications. Control of today's robots is often remote which requires even more advanced computer vision capabilities as well as sensors and interface techniques. Learning has become crucial for modern robotic systems as well. This new book deals with control and learning in robotic systems.