Extrinsic Dexterous Manipulation with a Direct-drive Hand: A Case Study
Abstract
This paper explores a novel approach to dexterous manipulation, aimed at levels of speed, precision, robustness, and simplicity suitable for practical deployment. The enabling technology is a Direct-drive Hand (DDHand) comprising two fingers, two DOFs each, that exhibit high speed and a light touch. The test application is the dexterous manipulation of three small and irregular parts, moving them to a grasp suitable for a subsequent assembly operation, regardless of initial presentation. We employed four primitive behaviors that use ground contact as a “third finger”, prior to or during the grasp process: pushing, pivoting, toppling, and squeeze-grasping. In our experiments, each part was presented from 30 to 90 times randomly positioned in each stable pose. Success rates varied from 83% to 100%. The time to manipulate and grasp was 6.32 seconds on average, varying from 2.07 to 16 seconds. In some cases, performance was robust, precise, and fast enough for practical applications, but in other cases, pose uncertainty required time-consuming vision and arm motions. The paper concludes with a discussion of further improvements required to make the primitives robust, eliminate uncertainty, and reduce this dependence on vision and arm motion.
BibTeX
@conference{Gupta-2022-134563,author = {Arnav Gupta and Yuemin Mao and Ankit Bhatia and Xianyi Cheng and Jonathan P. King and Yifan Hou and Matthew T. Mason},
title = {Extrinsic Dexterous Manipulation with a Direct-drive Hand: A Case Study},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2022},
month = {December},
publisher = {IEEE},
keywords = {Uncertainty, Robustness, Behavioral sciences, Intelligent robots},
}