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} }