Exploiting In-Hand Knowledge in Hybrid Joint-Cartesian Mapping for Anthropomorphic Robotic Hands

Replication of human hand motions on anthropomorphic robotic hands is typically treated in literature as the combination two sub-problems: measurement motions, and mapping such hand. In this letter we focus second one. Different approaches have been proposed to deal with problem, but none them preserves both master finger shapes fingertip positions hand, i.e. ensuring predictability natural motion for teleoperator. article, propose a novel hybrid approach that combines joint Cartesian mappings single solution. particular, exploit priori, in-hand information related areas workspace which thumb fingertips can get contact. This allows define, each finger, zone transition from mapping. As consequence, shape during volar grasps correctness precision are preserved, despite master-slave kinematic dissimilarities. The presented experimentally evaluated simulation real slave