A skeleton-based approach to grasp known objects with a humanoid robot

This paper is about grasping known objects of arbitrary shape with a humanoid robot. We extend our previous work, where we presented a grasp planning method using an object representation based on the medial axis transform (MAT). The MAT describes an object's topological skeleton and contains information about local symmetry properties and thickness valuable for grasp planning. So far, our previous work was only conducted in simulation. The contribution of this paper is the transfer of our grasp planning method to the real world. We present grasping experiments with challenging arbitrarily shaped objects where we execute the grasps generated by our grasp planner on a real humanoid robot with a five-finger hand.

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