Extraction of grasp-related features by human dual-hand object exploration

We consider the problem of objects exploration for grasping purposes, specifically in cases where vision based methods are not applicable. A novel dual-hand object exploration method is proposed that takes benefits from a human demonstration to enrich knowledge about an object. The user handles an object freely using both hands, without restricting the object pose. A set of grasp-related features obtained during exploration is demonstrated and utilized to generate grasp oriented bounding boxes that are basis for pre-grasp hypothesis. We believe that such exploration done in a natural and user friendly way creates important link between an operator intention and a robot action.