HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers

Y.-W. Chao et al., “HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers,” in IEEE International Conference on Robotics and Automation (ICRA), 2022, pp. 6941–6947, doi: 10.1109/ICRA46639.2022.9812302.

Abstract

We introduce a new simulation benchmark “Han-doverSim” 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. Code is open sourced at https://handover-sim.github.io.

BibTeX Entry

@inproceedings{chao2022handoversim,
  title = {HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers},
  author = {Chao, Yu-Wei and Paxton, Chris and Xiang, Yu and Yang, Wei and Sundaralingam, Balakumar and Chen, Tao and Murali, Adithyavairavan and Cakmak, Maya and Fox, Dieter},
  year = {2022},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  pages = {6941--6947},
  type = {conference},
  url = {https://ieeexplore.ieee.org/abstract/document/9812302},
  organization = {IEEE},
  doi = {10.1109/ICRA46639.2022.9812302}
}