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Abstract:
Table tennis is a difficult motor skill which requires all basic components
of a general motor skill learning system. In order to get a step closer to such
a generic approach to the automatic acquisition and refinement of table tennis, we
study table tennis from a human motor control point of view. We make use of the
basic models of discrete human movement phases, virtual hitting points, and the
operational timing hypothesis. Using these components, we create a computational
model which is aimed at reproducing human-like behavior. We verify the
functionality of this model in a physically realistic simulation of a BarrettWAM.
