Robust Object Grasping using Force Compliant Motion Primitives

We address the problem of grasping everyday objects that are small relative to an anthropomorphic hand, such as pens, screwdrivers, cellphones, and hammers from their natural poses on a support surface, e.g., a table top. In such conditions, state of the art grasp generation techniques fail to provide robust, achievable solutions due to either ignoring or trying to avoid contact with the support surface. In contrast, we show that contact with support surfaces is critical for grasping small objects. This also conforms with our anecdotal observations of human grasping behaviors. We develop a simple closed-loop hybrid controller that mimics this interactive, contact-rich strategy by a position-force, pre-grasp and landing strategy for finger placement. The approach uses a compliant control of the hand during the grasp and release of objects in order to preserve safety. We conducted extensive grasping experiments on a variety of small objects with similar shape and size. The results demonstrate that our approach is robust to localization uncertainties and applies to many everyday objects.