BiGym: A Demo-Driven Mobile Bi-Manual Manipulation Benchmark
Abstract
We introduce BiGym, a new benchmark and learning environment for mobile bi-manual demo-driven robotic manipulation. BiGym features 40 diverse tasks set in home environments, ranging from simple target reaching to complex kitchen cleaning. To capture the real-world performance accurately, we provide human-collected demonstrations for each task, reflecting the diverse modalities found in real-world robot trajectories. BiGym supports a variety of observations, including proprioceptive data and visual inputs such as RGB, and depth from 3 camera views. To validate the usability of BiGym, we thoroughly benchmark the state-of-the-art imitation learning algorithms and demo-driven reinforcement learning algorithms within the environment and discuss the future opportunities.
Cite
Text
Chernyadev et al. "BiGym: A Demo-Driven Mobile Bi-Manual Manipulation Benchmark." Proceedings of The 8th Conference on Robot Learning, 2024.Markdown
[Chernyadev et al. "BiGym: A Demo-Driven Mobile Bi-Manual Manipulation Benchmark." Proceedings of The 8th Conference on Robot Learning, 2024.](https://mlanthology.org/corl/2024/chernyadev2024corl-bigym/)BibTeX
@inproceedings{chernyadev2024corl-bigym,
title = {{BiGym: A Demo-Driven Mobile Bi-Manual Manipulation Benchmark}},
author = {Chernyadev, Nikita and Backshall, Nicholas and Ma, Xiao and Lu, Yunfan and Seo, Younggyo and James, Stephen},
booktitle = {Proceedings of The 8th Conference on Robot Learning},
year = {2024},
pages = {4201-4217},
volume = {270},
url = {https://mlanthology.org/corl/2024/chernyadev2024corl-bigym/}
}