A general tactile approach for grasping unknown objects with a humanoid robot

In this paper, we present a tactile approach to grasp large and unknown objects, which can not be easily manipulated with a single end-effector or two-handed grasps, with the whole upper body of a humanoid robot. Instead of conventional joint level force sensing, we equip the robot with various patches of HEX-o-SKIN - a self-organizing, multi-modal cellular artificial skin. Low-level controllers, one allocated to each sensor cell, utilize a self-explored inverted jacobian-like sensory-motor map to directly transfer tactile stimulation into reactive arm motions, altering basic grasping trajectories to the need of the current object. A high-level state machine guides those low-level controllers during the different states of the grasping action. Desired contact points, and key poses for the trajectory generation, are taught through forceless tactile stimulation. First experiments on a position controlled robot, an HRP-2 humanoid, demonstrate the feasibility of our approach. Our paper contributes to the first realization of a self-organizing tactile sensor-behavior mapping on a full-sized humanoid robot, which enables: 1) a new general approach for grasping unknown objects with the whole-body; and 2) a novel way of teaching behaviors using pre-contact tactile sensing.