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license: mit
tags:
- robotics
- imitation-learning
- rlds
- openvla
- libero
- boss-benchmark
---
# BOSS — RAMG-augmented demonstrations (RLDS)
The augmented training set behind Setup B of Table I in
[**BOSS**](https://arxiv.org/abs/2502.15679) (Yang et al., *IEEE RA-L*, 2025), in
RLDS/TFDS form so it can be fed
straight to OpenVLA fine-tuning.
- **56,945 episodes** across 1,727 modified tasks (the 44 BOSS skills, each with
one visual modification generated by the Rule-based Automatic Modification
Generator)
- 1,024 tfrecord shards, ~267 GB
Produced by replaying each original demonstration in its modified environment and
discarding failed replays, so the trajectory is unchanged and only the visual
observation differs.
## Usage
```shell
huggingface-cli download yygx/BOSS-data-augmentation --repo-type dataset \
--local-dir datasets
# from inside your OpenVLA checkout
DATASET_NAME=libero_bl3_all DATA_ROOT_DIR=./datasets \
bash ../integrations/openvla/shells/finetune_openvla.sh
```
## HDF5 form
The BC baselines read HDF5, not RLDS, and that form is **not** distributed here.
Regenerate it from the repository, which ships all 1,727 modified bddl files:
```shell
python RAMG/DA_demos_generation.py --benchmark data_augmentation
```
Roughly 6 minutes per task single-threaded; `--start-index N` resumes.
## Citation
```bibtex
@article{yang2025boss,
title={BOSS: Benchmark for observation space shift in long-horizon task},
author={Yang, Yue and Zhao, Linfeng and Ding, Mingyu and Bertasius, Gedas and Szafir, Daniel},
journal={IEEE Robotics and Automation Letters},
volume={10},
number={9},
pages={8882--8889},
year={2025},
publisher={IEEE}
}
```
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