VISUOMOTOR MAPS FOR ROBOT TASK LEARNING THROUGH IMITATION

Abstract We propose an approach that allows a robot to learn a task through imitation, using motor representations, as suggested by recent findings in neuro-science. The robot relies on a visuomotor mapto convert visual information into motor data. Then, by observing and imitating other agents, the robot can learn a set of elementary motions (motor vocabulary), that will eventually be used to compose more complex actions, for each specific task domain. We illustrate the approach in a mobile robotics task. Egomotion estimation is used as a visuomotor map, that allows the robot to learn a motor vocabulary for topological mapping and navigation. The approach can be extended to different robots and applications. Encouraging results are presented and discussed

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