How to think about grasping systems - basis grasps and variation budgets

Abstract

In unstructured environments, grasping systems should cope with a wide range of object and environment variations, across size, shape and pose, friction and mass, visual occlusions and shadows, robot control inaccuracy, and many other factors. This paper proposes a framework for analyzing the sources of variations in grasping tasks as a way to understand grasping system performance. The concomitant design approach starts with a collection of basis grasps, each a specific arrangement of the fingers on a specific object. Next, we use motion sequences, sensing, and passive mechanics to make these grasps robust to variations in objects, sensing, and control. We then analyze each grasp’s robustness to local variation to determine the basin of attraction, the range of variation it can tolerate while still achieving a good grasp. Finally, we treat this basin of attraction as a variation budget that can be distributed across subsystems to inform system tradeoffs between object variation, perception errors, and robot inaccuracies. The principle advantage is that within the context of specific grasps, the effects of local variations can be understood and quantified, and therefore compared across disparate approaches.