Price loading...

Learning for Adaptive and Reactive Robot Control: A Dynamical Systems Approach (Intelligent Robotics and Autonomous Agents series)

Multicolor

AI & Machine Learning

Price data last checked 102 day(s) ago - refreshing...

View at Amazon

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

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.

Product Specifications

Colour: Multicolor
Format: hardcover
ASIN: 0262046164
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 01 February 2022
Listed Since: 29 March 2021

Barcode

No barcode data available

Learning for Adaptive and Reactive Robot Control: A Dynamical Systems Approach (Intelligent Robotics and Autonomous Agents series)

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Human-Robot Interaction Control Using Reinforcement Learning (IEEE Press Series on Systems Science and Engineering)

Robot Learning Human Skills and Intelligent Control Design

Introduction to Autonomous Robots: Mechanisms, Sensors, Acutators, and Algorithms

Approaches to Probabilistic Model Learning for Mobile Manipulation Robots: 89 (Springer Tracts in Advanced Robotics, 89)

Dynamics and Control of Robotic Systems

Feedback Control of Dynamic Bipedal Robot Locomotion: 01 (Automation and Control Engineering)

Robotics and Automation Handbook

Adaptive Control for Robotic Manipulators

Adaptive Control for Robotic Manipulators

Reinforcement Learning and Dynamic Programming Using Function Approximators: 39 (Automation and Control Engineering)

Robot Intelligence: An Advanced Knowledge Processing Approach (Advanced Information and Knowledge Processing)

Adaptive and Learning-Based Control of Safety-Critical Systems (Synthesis Lectures on Computer Science)

Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents series)

Parallel Robots: Mechanics and Control

Advanced Technologies in Modern Robotic Applications

Adaptive Robust Control for Planar Snake Robots: 363 (Studies in Systems, Decision and Control, 363)

Tactile Sensing, Skill Learning, and Robotic Dexterous Manipulation

CRC Press Multiagent Robotic Systems - Computational Intelligence

Adaptive Control: Methods, Applications and Research (Systems Engineering Methods, Developments and Technology)

Lyapunov-Based Control of Robotic Systems: 36 (Automation and Control Engineering)

Dynamics And Control Systems (Mechanical Engineering Essentials with Python)

Designing Robot Behavior in Human-Robot Interactions

Springer Reinforcement Learning for Optimal Feedback Control

Springer - Reinforcement Learning for Optimal Feedback Control