Grasping Objects of Unknown Geometry with Tactile Feedback

Service robots operating in unconstrained environments like our homes need to be able to grasp and manipulate all kinds of objects, even if they are not known in advance. While many common approaches for grasping rely on detailed geometric models of the objects to perform a grasp optimization process in simulated scenes, we propose a model-free approach which relies on tactile feedback and coarse shape estimation from vision. Tactile sensor arrays continuously shrink in size and become available for small-size finger tips these days, allowing us to consider more natural approaches to grasping. Evaluating this grasping approach on two different hands, the anthropomorphic Shadow Dexterous Hand and the three-fingered Schunk Dexterous Hand, we prove the feasibility and portability of our method.