A grasp synthesis algorithm based on postural synergies for an anthropomorphic arm-hand robotic system

In this paper development, implementation and experimental validation of a grasp synthesis algorithm for an anthropomorphic robotic arm-hand system in a low dimensional posture subspace is proposed. The algorithm has been developed on the basis of the analysis of human hand postural synergies. Drawing inspiration from neuroscientific studies, a database of grasps has been created through the observation and the analysis of the human finger posture during reaching and grasping tasks of several objects. The optimal hand configuration and wrist pose have been determined by applying an optimization procedure grounded on a stochastic method. The grasp synthesis algorithm has been validated in simulation and on a real arm-hand robotic platform consisting of the KUKA LWR 4+ robot arm and the DLR-HIT Hand II. The experimental results have validated the hypothesis made during algorithm implementation and have shown that the armhand robotic platform is able to perform the hand preshaping configurations predicted by the grasp synthesis algorithm.

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