任意物体の反応型ヒューマン・トゥ・ロボット受け渡し
Reactive Human-to-Robot Handovers of Arbitrary Objects
視覚と閉ループ運動計画を組み合わせ、未知の多様な物体を人からロボットへリアルタイムに受け渡すシステムを提案し、26物体のベンチマークとユーザー研究で有効性を示した。
著者: Wei Yang, Chris Paxton, Arsalan Mousavian, Yu-Wei Chao, Maya Cakmak, Dieter Fox
分類: cs.RO, cs.CV
原文アブストラクト
Human-robot object handovers have been an actively studied area of robotics over the past decade; however, very few techniques and systems have addressed the challenge of handing over diverse objects with arbitrary appearance, size, shape, and rigidity. In this paper, we present a vision-based system that enables reactive human-to-robot handovers of unknown objects. Our approach combines closed-loop motion planning with real-time, temporally-consistent grasp generation to ensure reactivity and motion smoothness. Our system is robust to different object positions and orientations, and can grasp both rigid and non-rigid objects. We demonstrate the generalizability, usability, and robustness of our approach on a novel benchmark set of 26 diverse household objects, a user study with naive users (N=6) handing over a subset of 15 objects, and a systematic evaluation examining different ways of handing objects. More results and videos can be found at https://sites.google.com/nvidia.com/handovers-of-arbitrary-objects.
