In this work we present a method to produce a model of human motion based on an expansion in functions series. The model is thought to reproduce the learned movements generalizing them to different conditions. We will show, with an example, how the proposed method is capable to produce the model from a reduced set of examples preserving the relevant features of the demonstrations while guaranteeing constraints at boundaries.
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