title: From Visuo-Motor Development to Low-level Imitation creator: Andry, Pierre creator: Gaussier, Philippe creator: Nadel, Jacqueline subject: Machine Learning subject: Neural Nets subject: Robotics description: 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. publisher: Lund University Cognitive Studies contributor: Prince, Christopher G. contributor: Demiris, Yiannis contributor: Marom, Yuval contributor: Kozima, Hideki contributor: Balkenius, Christian date: 2002 type: Conference Paper type: PeerReviewed format: application/pdf identifier: http://cogprints.org/2500/1/Andry.pdf identifier: Andry, Pierre and Gaussier, Philippe and Nadel, Jacqueline (2002) From Visuo-Motor Development to Low-level Imitation. [Conference Paper] relation: http://cogprints.org/2500/