Emil Hyttinen

Learning the tactile signatures of prototypical object parts for robust part-based grasping of novel objects

We present a robotic agent that learns to derive object grasp stability from touch. The main contribution of our work is the use of a characterization of the shape of the part of the object that is enclosed by the gripper to condition the tactile-based stability model. As a result, the agent is able…