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From Visuo-Motor Development to Low-level Imitation

By Pierre Andry, Philippe Gaussier and Jacqueline Nadel

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

Topics: Machine Learning, Neural Nets, Robotics
Publisher: Lund University Cognitive Studies
Year: 2002
OAI identifier: oai:cogprints.org:2500

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