In this paper, we discuss a methodology to extract play primitives, defined as a sequence of low-level motion behaviors identified during a playing action, such as stacking or inserting a toy. Our premise is that if a robot could interpret the basic movements of a human's play, it will be able to interact with many different kinds of toys, in conjunction with its human playmate. As such, we present a method that combines motion behavior analysis and behavior sequencing, which capitalizes on the inherent characteristics found in the dynamics of play such as the limited domain of the objects and manipulation skills required. In this paper, we give details on the approach and present results from applying the methodology to a number of play scenarios.
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