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HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers
HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers
1NVIDIA, 2UT Dallas, 3MIT CSAIL, 4University of Washington
IEEE International Conference on Robotics and Automation (ICRA), 2022
Abstract
We introduce a new simulation benchmark "HandoverSim" for human-to-robot object handovers. To simulate the giver's motion, we leverage a recent motion capture dataset of hand grasping of objects. We create training and evaluation environments for the receiver with standardized protocols and metrics. We analyze the performance of a set of baselines and show a correlation with a real-world evaluation.
Paper
Citing HandoverSim
Please cite HandoverSim if it helps your research:
@INPROCEEDINGS{chao:icra2022,
author = {Yu-Wei Chao and Chris Paxton and Yu Xiang and Wei Yang and Balakumar Sundaralingam and Tao Chen and Adithyavairavan Murali and Maya Cakmak and Dieter Fox},
booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
title = {{HandoverSim}: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers},
year = {2022},
}Code
Handover-Sim
A simulation environment and benchmark for human-to-robot object handovers
EasySim
A library for creating Gym environments with unified API to various physics simulatorsVideo
Contact
Send any comments or questions to Yu-Wei Chao: ychao@nvidia.com.
Last updated on 2022/06/05