yygx/BOSS-data-augmentation

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}
}