Reactive Human-to-Robot Handovers of Arbitrary Objects

• URL: http://arxiv.org/abs/2011.08961v2
• Date: Thu, 3 Jun 2021 20:48:44 GMT
• Title: Reactive Human-to-Robot Handovers of Arbitrary Objects
• Authors: Wei Yang, Chris Paxton, Arsalan Mousavian, Yu-Wei Chao, Maya Cakmak, Dieter Fox
• Abstract summary: We present a vision-based system that enables human-to-robot handovers of unknown objects. Our approach combines closed-loop motion planning with real-time, temporally-consistent grasp generation. We demonstrate the generalizability, usability, and robustness of our approach on a novel benchmark set of 26 diverse household objects.
• Score: 57.845894608577495
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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