触覚データ推定による未知物体の適応的把持
Estimating Tactile Data for Adaptive Grasping of Novel Objects
未知物体に対して、現在の把持近傍の触覚データをシミュレーションで推定し、把持の成功率を評価することで安定した把持へ適応する手法を提案。YCB物体セットで88%の成功率を達成した。
著者: Emil Hyttinen, Danica Kragic, Renaud Detry
分類: cs.RO
原文アブストラクト
We present an adaptive grasping method that finds stable grasps on novel objects. The main contributions of this paper is in the computation of the probability of success of grasps in the vicinity of an already applied grasp. Our method performs grasp adaptions by simulating tactile data for grasps in the vicinity of the current grasp. The simulated data is used to evaluate hypothetical grasps and thereby guide us toward better grasps. We demonstrate the applicability of our method by constructing a system that can plan, apply and adapt grasps on novel objects. Experiments are conducted on objects from the YCB object set and the success rate of our method is 88%. Our experiments show that the application of our grasp adaption method improves grasp stability significantly.
