微分可能なフォースクロージャ推定器による任意のハンド構造での多様かつ物理的に安定な把持の合成
Synthesizing Diverse and Physically Stable Grasps with Arbitrary Hand Structures using Differentiable Force Closure Estimator
フォースクロージャを高速に微分可能な形で推定する手法を提案し、訓練データなしで任意のハンド構造に対し多様で物理的に安定な把持を合成できるようにした。
著者: Tengyu Liu, Zeyu Liu, Ziyuan Jiao, Yixin Zhu, Song-Chun Zhu
分類: cs.RO
原文アブストラクト
Existing grasp synthesis methods are either analytical or data-driven. The former one is oftentimes limited to specific application scope. The latter one depends heavily on demonstrations, thus suffers from generalization issues; e.g., models trained with human grasp data would be difficult to transfer to 3-finger grippers. To tackle these deficiencies, we formulate a fast and differentiable force closure estimation method, capable of producing diverse and physically stable grasps with arbitrary hand structures, without any training data. Although force closure has commonly served as a measure of grasp quality, it has not been widely adopted as an optimization objective for grasp synthesis primarily due to its high computational complexity; in comparison, the proposed differentiable method can test a force closure within milliseconds. In experiments, we validate the proposed method's efficacy in 6 different settings.
