Robot Programming by Demonstration: 1st Edition (Hardback) book cover

Robot Programming by Demonstration

1st Edition

By Sylvain Calinon

EPFL Press

320 pages

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Hardback: 9781439808672
pub: 2009-08-24
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Description

Also referred to as learning by imitation, tutelage, or apprenticeship learning, Programming by Demonstration (PbD) develops methods by which new skills can be transmitted to a robot. This book examines methods by which robots learn new skills through human guidance. Taking a practical perspective, it covers a broad range of applications, including service robots. The text addresses the challenges involved in investigating methods by which PbD is used to provide robots with a generic and adaptive model of control. Drawing on findings from robot control, human-robot interaction, applied machine learning, artificial intelligence, and developmental and cognitive psychology, the book contains a large set of didactic and illustrative examples. Practical and comprehensive machine learning source codes are available on the book’s companion website: http://www.programming-by-demonstration.org

Table of Contents

ACKNOWLEDGMENT

INTRODUCTION

Contributions

Organization of the book

Review of Robot Programming by Demonstration (PBD)

Current state of the art in PbD

SYSTEM ARCHITECTURE

Illustration of the proposed probabilistic approach

Encoding of motion in a Gaussian Mixture Model (GMM)

Encoding of motion in Hidden Markov Model (HMM)

Reproduction through Gaussian Mixture Regression (GMR)

Reproduction by considering multiple constraints

Learning of model parameters

Reduction of dimensionality and latent space projection

Model selection and initialization

Regularization of GMM parameters

Use of prior information to speed up the learning process

Extension to mixture models of varying density distributions

Summary of the chapter

COMPARISON AND OPTIMIZATION OF THE PARAMETERS

Optimal reproduction of trajectories through HMM and GMM/GMR

Optimal latent space of motion

Optimal selection of the number of Gaussians

Robustness evaluation of the incremental learning process

HANDLING OF CONSTRAINTS IN JOINT SPACE AND TASK SPACE

Inverse kinematics

Handling of task constraints in joint spaceexperiment with industrial robot

Handling of task constraints in latent spaceexperiment with humanoid robot

EXTENSION TO DYNAMICAL SYSTEM AND HANDLING OF PERTURBATIONS

Proposed dynamical system

Influence of the dynamical system parameters

Experimental setup

Experimental results

TRANSFERRING SKILLS THROUGH ACTIVE TEACHING METHODS

Experimental setup

Experimental results

Roles of an active teaching scenario

USING SOCIAL CUES TO SPEED UP THE LEARNING PROCESS

Experimental setup

Experimental results

DISCUSSION, FUTURE WORK AND CONCLUSIONS

Advantages of the proposed approach

Failures and limitations of the proposed approach

Further issues

Final words

REFERENCES

INDEX

Subject Categories

BISAC Subject Codes/Headings:
COM051240
COMPUTERS / Software Development & Engineering / Systems Analysis & Design
TEC007000
TECHNOLOGY & ENGINEERING / Electrical