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Learning the velocity kinematics of ICUB for model-based control: XCSF versus LWPR

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5 Author(s)
Guillaume Sicard ; Université Pierre et Marie Curie, Institut des Systèmes Intelligents et de Robotique - CNRS UMR 7222, Pyramide Tour 55 - Boite Courrier 173, 4 Place Jussieu, 75252 Paris CEDEX 5, France ; Camille Salaün ; Serena Ivaldi ; Vincent Padois
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The model-based control of humanoid robots requires the availability of accurate mechanical models that can be hard to obtain in practice. One approach to this problem consists in calling upon machine learning methods. In this paper, using a standard control approach based on visual servoing, we compare the accuracy of two supervised learning methods, namely LWPR and XCSF, to extract the forward velocity kinematics of the upper body of the iCub robot. Experiments are performed in simulation, using one arm and the head for reaching tasks. We show that both methods provide accurate models of the robot, with a slight advantage to XCSF over LWPR.

Published in:

Humanoid Robots (Humanoids), 2011 11th IEEE-RAS International Conference on

Date of Conference:

26-28 Oct. 2011