metadata
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 (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
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:
python RAMG/DA_demos_generation.py --benchmark data_augmentation
Roughly 6 minutes per task single-threaded; --start-index N resumes.
Citation
@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}
}