Dynamics And Robust Control Of Robot Environment Interaction

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.

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.

This self-contained introduction to practical robot kinematics and dynamics includes a comprehensive treatment of robot control. It provides background material on terminology and linear transformations, followed by coverage of kinematics and inverse kinematics, dynamics, manipulator control, robust control, force control, use of feedback in nonlinear systems, and adaptive control. Each topic is supported by examples of specific applications. Derivations and proofs are included in many cases. The book includes many worked examples, examples illustrating all aspects of the theory, and problems.

Embark on an Enlightening Journey to "Mastering Robot Dynamics" In a world driven by automation and robotics, mastering the intricacies of robot dynamics is pivotal for creating advanced robotic systems that move with precision and intelligence. "Mastering Robot Dynamics" is your ultimate guide to navigating the complex world of robot motion, control, and manipulation. Whether you're an engineer, researcher, robotics enthusiast, or student, this book equips you with the knowledge and skills needed to excel in designing and controlling sophisticated robotic mechanisms. About the Book: "Mastering Robot Dynamics" takes you on a transformative journey through the intricacies of robot motion and control, from foundational concepts to advanced techniques. From kinematics and dynamics to trajectory planning and real-time control, this book covers it all. Each chapter is meticulously designed to provide both a deep understanding of the principles and practical applications in real-world robotic scenarios. Key Features: · Foundational Understanding: Build a solid foundation by comprehending the core principles of robot dynamics, including kinematics, inertia, and motion equations. · Robot Kinematics: Explore forward and inverse kinematics, understanding how robots move and calculating joint configurations. · Robot Dynamics: Dive into the study of forces, torques, and motion equations, learning how robots interact with their environments. · Trajectory Planning: Master the art of planning robot paths and trajectories, considering constraints and optimizing motion sequences. · Sensors and Perception: Gain insights into sensor integration, perception systems, and how robots interact with the world through feedback. · Motion Control: Learn about different types of control strategies, from PID control to advanced techniques like model predictive control. · Collision Avoidance: Understand methods for detecting and avoiding collisions, ensuring safety and reliability in robot operations. · Robot Manipulation: Explore techniques for manipulating objects, including grasp planning, manipulation tasks, and robotic arms. · Challenges and Trends: Discover challenges in robot dynamics, from sensor noise to complex control algorithms, and explore emerging trends shaping the future of robotics. Who This Book Is For: "Mastering Robot Dynamics" is designed for engineers, researchers, robotics enthusiasts, students, and anyone passionate about robotics. Whether you're aiming to enhance your skills or embark on a journey toward becoming a robotics expert, this book provides the insights and tools to navigate the complexities of designing and controlling robotic systems. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Robust Control of Robots bridges the gap between robust control theory and applications, with a special focus on robotic manipulators. It is divided into three parts: robust control of regular, fully-actuated robotic manipulators; robust post-failure control of robotic manipulators; and robust control of cooperative robotic manipulators. In each chapter the mathematical concepts are illustrated with experimental results obtained with a two-manipulator system. They are presented in enough detail to allow readers to implement the concepts in their own systems, or in Control Environment for Robots, a MATLAB®-based simulation program freely available from the authors. The target audience for Robust Control of Robots includes researchers, practicing engineers, and graduate students interested in implementing robust and fault tolerant control methodologies to robotic manipulators.

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.

A comprehensive guide to the friction, contact and impact on robot control and force feedback mechanism Dynamics and Control of Robotic Manipulators with Contact and Friction offers an authoritative guide to the basic principles of robot dynamics and control with a focus on contact and friction. The authors discuss problems in interaction between human and real or virtual robot where dynamics with friction and contact are relevant. The book fills a void in the literature with a need for a text that considers the contact and friction generated in robot joints during their movements. Designed as a practical resource, the text provides the information needed for task planning in view of contact, impact and friction for the designer of a robot control system for high accuracy and long durability. The authors include a review of the most up-to-date advancements in robot dynamics and control. It contains a comprehensive resource to the effective design and fabrication of robot systems and components for engineering and scientific purposes. This important guide: Offers a comprehensive reference with systematic treatment and a unified framework Includes simulation and experiments used in dynamics and control of robot considering contact, impact and friction Discusses the most current tribology methodology used to treat the multiple–scale effects Contains valuable descriptions of experiments and software used Presents illustrative accounts on the methods employed to handle friction in the closed loop, including the principles, implementation, application scope, merits and demerits Offers a cohesive treatment that covers tribology and multi-scales, multi-physics and nonlinear stochastic dynamics control Written for graduate students of robotics, mechatronics, mechanical engineering, tracking control and practicing professionals and industrial researchers, Dynamics and Control of Robotic Manipulators with Contact and Friction offers a review to effective design and fabrication of stable and durable robot system and components.