Robot Programming by Demonstration

Author:   Sylvain Calinon (Learning Algorithms and Systems Laboratory, Switzerland)
Publisher:   Taylor & Francis Inc
ISBN:  

9781439808672


Pages:   320
Publication Date:   15 April 2021
Format:   Hardback
Availability:   Out of stock   Availability explained
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Robot Programming by Demonstration


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Author:   Sylvain Calinon (Learning Algorithms and Systems Laboratory, Switzerland)
Publisher:   Taylor & Francis Inc
Imprint:   Taylor & Francis Inc
Dimensions:   Width: 16.80cm , Height: 1.80cm , Length: 24.60cm
Weight:   0.612kg
ISBN:  

9781439808672


ISBN 10:   1439808678
Pages:   320
Publication Date:   15 April 2021
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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

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Learning Algorithms and Systems Laboratory, Switzerland

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