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Publication Details

Reference TypeJournal Article
Author(s)Billard, A.;Epars, Y.;Calinon, S.;Cheng, G.;Schaal, S.
TitleDiscovering optimal imitation strategies
Journal/Conference/Book TitleRobotics and Autonomous Systems
Keywordsimitation, intent extraction, motor control
AbstractThis paper develops a general policy for learning relevant features of an imitation task. We restrict our study to imitation of manipulative tasks or of gestures. The imitation process is modeled as a hierarchical optimization system, which minimizes the discrepancy between two multi-dimensional datasets. To classify across manipulation strategies, we apply a probabilistic analysis to data in Cartesian and joint spaces. We determine a general metric that optimizes the policy of task reproduction, following strategy determination. The model successfully discovers strategies in six different imitative tasks and controls task reproduction by a full body humanoid robot.
Short TitleDiscovering optimal imitation strategies

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