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Catching Objects in Flight

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Published on Oct 10, 2013

We target the difficult problem of catching in-flight objects with uneven shapes. This requires the solution of three complex problems: predicting accurately the trajectory of fastmoving
objects, predicting the feasible catching configuration and planning the arm motion, all within milliseconds. We follow a programming-by-demonstration approach in order to learn models of the object and arm dynamics from throwing examples. We propose a new methodology for finding a feasible catching configuration in a probabilistic manner. We leverage the
strength of dynamical systems for encoding motion from several demonstrations. This enables fast and on-line adaptation of the arm motion in the presence of sensor uncertainty. We validate the approach in simulation with the iCub humanoid robot and in real-world experiment with the KUKA LWR 4+ (7 degrees of freedom arm robot) for catching a hammer, a tennis racket, a empty bottle, a partially filled bottle and a cardboard box.

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