creators_name: Andry, Pierre
creators_name: Gaussier, Philippe
creators_name: Nadel, Jacqueline
editors_name: Prince, Christopher G.
editors_name: Demiris, Yiannis
editors_name: Marom, Yuval
editors_name: Kozima, Hideki
editors_name: Balkenius, Christian
type: confpaper
datestamp: 2003-09-26
lastmod: 2011-03-11 08:55:03
metadata_visibility: show
title: From Visuo-Motor Development to Low-level Imitation
ispublished: pub
subjects: comp-sci-mach-learn
subjects: comp-sci-neural-nets
subjects: comp-sci-robot
full_text_status: public
keywords: robotics, neural network, self-organization, imitation
abstract: We present the first stages of the developmental course of a robot using vision and a 5 degree of freedom robotic arm. During an exploratory behavior, the robot learns visuo-motor control of its mechanical arm. We show how a simple neural network architecture, combining elementary vision, a self-organized algorithm, and dynamical Neural Fields is able to learn and use proper associations between vision and arm movements, even if the problem is ill posed (2-D toward 3-D mapping and also mechanical redundancy between different joints). Highlighting the generic aspect of such an architecture, we show as a robotic result that it is used as a basis for simple gestural imitations of humans. Finally we show how the imitative mechanism carries on the developmental course, allowing the acquisition of more and more complex behavioral capabilities.
date: 2002
date_type: published
volume: 94
publisher: Lund University Cognitive Studies
pagerange: 7-15
refereed: TRUE
citation:   Andry, Pierre and Gaussier, Philippe and Nadel, Jacqueline  (2002) From Visuo-Motor Development to Low-level Imitation.  [Conference Paper]     
document_url: http://cogprints.org/2500/1/Andry.pdf