English

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

Robotics 2022-05-20 v1 Computer Vision and Pattern Recognition

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. Code is open sourced at https://handover-sim.github.io.

Keywords

Cite

@article{arxiv.2205.09747,
  title  = {HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers},
  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},
  journal= {arXiv preprint arXiv:2205.09747},
  year   = {2022}
}

Comments

Accepted to ICRA 2022

R2 v1 2026-06-24T11:22:41.038Z