LEARNING FOR ADAPTIVE AND REACTIVE ROBOT CONTROL: A DYNAMICAL SYSTEMS APPROACH

AUDE BILLARD, SINA MIRRAZAVI AND NADIA FIGUEROA

ISBN 10: 0262046164 / ISBN 13: 9780262046169

Edité par MIT PRESS, 2022

A propos de cet article

Brand New! Fast Delivery USA Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-14 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability. N° de réf. du vendeur Adh 9780262046169

Détails bibliographiques

Titre : LEARNING FOR ADAPTIVE AND REACTIVE ROBOT ...

Éditeur : MIT PRESS

Date d'édition : 2022

Reliure : Hardcover

Etat : NEW

A propos de ce titre

Synopsis :

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.

 
 

À propos de l?auteur:

Aude Billard is Professor, School of Engineering, Ecole Polytechnique Federale de Lausanne (EPFL) and Director of the Learning Algorithms and Systems Laboratory (LASA). Sina Mirrazavi is a Senior Researcher at Sony. Nadia Figueroa is the Shalini and Rajeev Misra Presidential Assistant Professor in the Mechanical Engineering and Applied Mechanics (MEAM) Department at the University of Pennsylvania.