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

PDF

arXiv

@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 simulators

Video

Contact

Send any comments or questions to Yu-Wei Chao: ychao@nvidia.com.