Unsupervised learning of simultaneous motor primitives through imitation
Abstract
We propose to build a system able to learn motor primitives from simultaneous demonstrations of several such primitives. Our approach is based on compact local descriptors of the motor trajectory similar to those used to learn acoustic words amongst sentences or objects inside visual scenes.
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mangin.2011.icdl.pdf (694.62 Ko)
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