The inherent uncertainty associated with unstructured environments makes establishing a successful grasp difficult. Traditional approaches to this problem involve hands that are complex, fragile, require elaborate sensor suites, and are difficult to control. Alternatively, by carefully designing the mechanical structure of the hand to incorporate features such as compliance and adaptability, the uncertainty inherent in unstructured grasping tasks can be more easily accommodated. In this paper, we demonstrate a novel adaptive and compliant grasper that can grasp objects spanning a wide range of size, shape, mass, and position/orientation using only a single actuator. The hand is constructed using polymer-based Shape Deposition Manufacturing (SDM) and has superior robustness properties, making it able to withstand large impacts without damage. We also present the results of two experiments to demonstrate that the SDM Hand can reliably grasp objects in the presence of large positioning errors, while keeping acquisition contact forces low. In the first, we evaluate the amount of allowable manipulator positioning error that results in a successful grasp. In the second experiment, the hand autonomously grasps a wide range of spherical objects positioned randomly across the workspace, guided by only a single image from an overhead camera, using feed-forward control of the hand.
Dollar et al. (2010) studied this question.