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8 - Learning of gestures by imitation in a humanoid robot

Published online by Cambridge University Press:  10 December 2009

By
Sylvain Calinon  and
Aude Billard
Edited by
Chrystopher L. Nehaniv  and
Kerstin Dautenhahn
Sylvain Calinon
Affiliation:
Swiss Federal Institute of Technology Lausanne (EPFL), Autonomous Systems Lab, Switzerland
Aude Billard
Affiliation:
Swiss Federal Institute of Technology Lausanne (EPFL), Autonomous Systems Lab, Switzerland
Chrystopher L. Nehaniv
Affiliation:
University of Hertfordshire
Kerstin Dautenhahn
Affiliation:
University of Hertfordshire
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Summary

Introduction

Traditionally, robotics developed highly specific controllers for the robot to perform a specific set of tasks in highly constrained and deterministic environments. This required the embedding of the controller with an extensive knowledge of the robot's architecture and of its environment. It was soon clear that such an approach would not scale up for controlling robots with multiple degrees of freedom, working in highly variable environments, such as humanoid robots required to interact with humans in their daily environment. The field has now moved to developing more flexible and adaptive control systems, so that the robot would no longer be dedicated to a single task, and could be re-programmed in a fast and efficient manner, to match the end-user needs.

Robot learning by imitation, also referred to as robot programming by demonstration, explores novel means of implicitly teaching a robot new motor skills (Billard and Siegwart, 2004; Dillmann, 2004; Schaal et al., 2003). This field of research takes inspiration in a large and interdisciplinary body of literature on imitation learning, drawing from studies in psychology, ethology and the neurosciences (Demiris and Hayes, 2001; Billard and Hayes, 1999; Alissandrakis et al., 2002). To provide a robot with the ability to imitate is advantageous for at least two reasons: it provides a natural, user-friendly means of implicitly programming the robot; it constrains the search space of motor learning by showing possible and/or optimal solutions.

In this chapter, we explore the issue of recognizing, generalizing and reproducing arbitrary gesture (Billard et al., 2004).

Type
Chapter
Information
Imitation and Social Learning in Robots, Humans and Animals
Behavioural, Social and Communicative Dimensions
 , pp. 153 - 178
Publisher: Cambridge University Press
Print publication year: 2007

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References

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