The Highly Adaptive SDM Hand: Design and Performance Evaluation

TLDR

Unstructured environments create uncertainty that makes grasping difficult, and traditional solutions are complex, fragile, and sensor‑heavy, whereas designing compliant, adaptable mechanical structures can better accommodate this uncertainty. This work introduces a novel adaptive, compliant grasper capable of grasping objects of diverse size, shape, mass, and orientation using only a single actuator. The hand is fabricated via polymer‑based Shape Deposition Manufacturing, yielding robust, impact‑resistant performance, and is evaluated through experiments that test positioning‑error tolerance and autonomous grasping guided by a single overhead camera image. Results demonstrate that the SDM Hand reliably grasps objects despite large positioning errors while maintaining low contact forces.

Abstract

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.