Application of Bayesian Optimization in Gripper Design for Effective Grasping

IF 3.4 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Marco Todescato;Dominik T. Matt;Andrea Giusti
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引用次数: 0

Abstract

Despite many recent technological advancements, grasping remains a challenging open problem in robotic manipulation. In contrast with most research which focuses equipping grippers with varying degree of intelligence, we approach grasping from a gripper design perspective, aiming to find the best tool for grasping a specific set of objects. Building on our previous work, this paper reviews a suitable parametrization for the geometry of two common families of industrial grippers and presents a grasp score beneficial for gripper design. We then formally cast the problem of finding the best gripper parametrization within a probabilistic framework, addressing it using Bayesian Optimization tools. Numerical results on a set of industrial objects demonstrate the effectiveness of the approach showing up to $\approx 300 \%$ improvement compared to the performance obtained using a fixed set of grippers.
贝叶斯优化在有效抓取夹具设计中的应用
尽管最近有许多技术进步,抓取仍然是机器人操作中一个具有挑战性的开放问题。与大多数研究侧重于装备不同程度的智能抓取器不同,我们从抓取器设计的角度来研究抓取,旨在找到抓取特定对象集的最佳工具。本文在前人工作的基础上,回顾了两种常见工业夹具的几何参数化,并提出了有利于夹具设计的夹具分数。然后,我们在概率框架内正式抛出寻找最佳夹持器参数化的问题,使用贝叶斯优化工具解决它。一组工业对象的数值结果证明了该方法的有效性,与使用一组固定夹具获得的性能相比,该方法的性能提高了约300%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Access
IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍: IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest. IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on: Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals. Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering. Development of new or improved fabrication or manufacturing techniques. Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.
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