Dexterous reaching, grasp transfer and planning using electrostatic representations

We propose a novel approach to transfer reach and grasp movements while being agnostic and invariant to finger kinematics, hand configurations and relative changes in object dimensions. We exploit a novel representation based on electrostatics to parametrise the salient aspects of the demonstrated grasp. By working in this alternate space that focuses on the relational aspects of the grasp rather than absolute kinematics, we are able to use inference based planning techniques to couple the motion in abstract spaces with trajectories in the configuration space of the robot. We demonstrate that our method computes stable grasps that generalise over objects of different shapes and robots of dissimilar kinematics while retaining the qualitative grasp type - all without expensive collision detection or re-optimisation.