快速计算最优抓取接触区域，提升机器人抓握鲁棒性
Fast Estimation of Globally Optimal Independent Contact Regions for Robust Grasping and Manipulation
- 基于增量式三维德尔劳奈三角剖分的分治算法
- 相比现有方法提速超100倍，且结果有理论误差上限
- 适合需要高效抓取规划的机器人系统开发者
本文提出一种快速的任意时间算法，用于计算全局最优独立接触区域（ICRs）。ICRs指每个区域内任一点接触即可形成有效抓握，其位置可为抓取与操作规划、学习及策略迁移提供指导。然而由于搜索空间随接触数呈指数增长，现代应用中对ICRs的研究甚少。本工作基于增量n维德尔劳奈三角剖分，提出分治算法，在足够实时时间内获得具有边界子优性的结果。论文聚焦于接触点位于平面内的抓取场景。实验表明，该方法在抓取质量上优于现有指标，相较竞品计算速度提升100倍以上。同时评估了基于ICRs引导策略的鲁棒性，并指明向3D通用实现的路径。代码将在发表后公开。
原文摘要 · Abstract (English)
This work presents a fast anytime algorithm for computing globally optimal independent contact regions (ICRs). ICRs are regions such that one contact within each region enables a valid grasp. Locations of ICRs can provide guidance for grasp and manipulation planning, learning, and policy transfer. However, ICRs for modern applications have been little explored, in part due to the expense of computing them, as they have a search space exponential in the number of contacts. We present a divide and conquer algorithm based on incremental n-dimensional Delaunay triangulation that produces results with bounded suboptimality in times sufficient for real-time planning. This paper presents the base algorithm for grasps where contacts lie within a plane. Our experiments show substantial benefits over competing grasp quality metrics and speedups of 100X and more for competing approaches to computing ICRs. We explore robustness of a policy guided by ICRs and outline a path to general 3D implementation. Code will be released on publication to facilitate further development and applications.
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