metadata
language:
- en
license: mit
task_categories:
- robotics
pretty_name: BRS Data
tags:
- robot-manipulation
- imitation-learning
- real-world-data
Dataset Card for BEHAVIOR Robot Suite (BRS) Data
This dataset provides robotic trajectories for five real-world household tasks. These tasks are:
- Clean house after a wild party;
- Clean the toilet;
- Take trash outside;
- Put items onto shelves;
- Lay clothes out.
These data are first collected and used in the paper BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities .
Dataset Details
Dataset Description
- Curated by: Yunfan Jiang
- License: MIT
Dataset Sources
- Repository: https://github.com/behavior-robot-suite/brs-algo
- Paper: https://arxiv.org/abs/2503.05652
- Project page: https://behavior-robot-suite.github.io/
Uses
For usage instructions, see our doc here.
Sample Usage
To train a WB-VIMA policy, simply run the following command as described in the official documentation:
python3 main/train/train.py data_dir=<HDF5_PATH> \
bs=<BS> \
arch=wbvima \
task=<TASK_NAME> \
exp_root_dir=<EXP_ROOT_DIR> \
gpus=<NUM_GPUS> \
use_wandb=<USE_WANDB> \
wandb_project=<WANDB_PROJECT>
To deploy a WB-VIMA policy on the real robot, simply run the following command:
python3 main/rollout/<TASK_NAME>/rollout_async.py --ckpt_path <CKPT_PATH> --action_execute_start_idx <IDX>
Citation
BibTeX:
@article{jiang2025brs,
title = {BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities},
author = {Yunfan Jiang and Ruohan Zhang and Josiah Wong and Chen Wang and Yanjie Ze and Hang Yin and Cem Gokmen and Shuran Song and Jiajun Wu and Li Fei-Fei},
year = {2025},
journal = {arXiv preprint arXiv: 2503.05652}
}