| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: BARX Raw HDF5 Demonstrations |
| size_categories: |
| - 10K<n<100K |
| tags: |
| - robotics |
| - imitation-learning |
| - hdf5 |
| - robocasa |
| - mimicgen |
| - barx |
| --- |
| |
| # BARX Raw HDF5 Demonstrations |
|
|
| This repository contains the normalized raw simulator demonstrations released |
| with **BARX: Cross-Embodiment Transfer via Behavior-Aligned Representations**. |
| It is intended for users who want to inspect the source trajectories, convert |
| them into another training format, reproduce the BARX RLDS conversion, or |
| prepare source demonstrations for new data-generation work. |
|
|
| ## Dataset summary |
|
|
| - **23,400 demonstrations** in **240 HDF5 files** |
| - approximately **284.03 GiB** |
| - **22,800 MimicGen-generated** demonstrations and **600 human-teleoperated |
| simulator** demonstrations |
| - six embodiments: IIWA, Jaco, Kinova3, Panda, Panda-OG, and UR5e |
| - four tasks with 5,850 demonstrations each: pick-and-place counter-to-sink, |
| pick-and-place sink-to-counter, turn-on-sink-faucet, and flip-mug-upright |
| - paper subsets: XP-900, XP-3K, SP-900, and target-50 |
|
|
| The human subset records simulated robot teleoperation; it contains no camera |
| recordings or personal information from the human operators. |
|
|
| ## Repository layout |
|
|
| ```text |
| human/ # 12 target/task files, 50 demonstrations each |
| mg/ # 228 generated files, 100 demonstrations each |
| manifest.csv # paths, sizes, SHA-256 hashes, metadata, and paper sets |
| ``` |
|
|
| Each file stores demonstrations below `data/demo_*`. Principal fields include: |
|
|
| - `actions`: `[T, 12]` canonical simulator actions; |
| - `states`: simulator states for replay and data generation; |
| - `obs/agentview_rgb`: `[T, 180, 320, 3]` RGB observations; |
| - `obs/ee_states` and `obs/gripper_states`: policy state inputs; |
| - `aux_info/eef_normalized_image_pts` and `aux_info/bboxes_2d/*`: BARX |
| representation annotations; and |
| - `ep_meta`: JSON episode metadata including the language instruction. |
|
|
| The canonical action layout is |
| `[arm(6), gripper(1), base(3), torso(1), mode(1)]`. Stored simulator asset paths |
| use the portable `<ROBOCASA>/` token rather than installation-specific paths. |
|
|
| ## Download and verification |
|
|
| Download the full repository with the Hugging Face CLI: |
|
|
| ```bash |
| hf download ajaysri/barx-raw-hdf5 --repo-type dataset --local-dir barx-raw-hdf5 |
| ``` |
|
|
| The BARX code release provides a manifest-driven verifier and RLDS converter. |
| See the [BARX project page](https://ajaysridhar.com/barx/) for the release code, |
| installation instructions, and pinned dataset revision. |
|
|
| ## Intended use |
|
|
| The dataset is intended for robotics and imitation-learning research, |
| cross-embodiment representation learning, format conversion, simulator replay, |
| and preparation of new data-generation pipelines. Users should preserve the |
| included attribution and cite BARX and RoboCasa in resulting work. |
|
|
| ## Limitations |
|
|
| - These are simulator demonstrations and do not directly characterize |
| real-world robot performance. |
| - The task and embodiment distribution is intentionally narrow and should not |
| be treated as a general-purpose robotics corpus. |
| - The raw demonstrations preserve the information needed to prepare MimicGen |
| source datasets, but the separately pinned BARX MimicGen generator and task |
| configurations are required for end-to-end regeneration. |
| - HDF5 is provided for exact source preservation and flexible conversion; the |
| processed BARX RLDS repositories are more convenient for policy training. |
|
|
| ## License and attribution |
|
|
| The BARX dataset is released under the |
| [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/). |
| Rendered simulator observations incorporate RoboCasa environments and assets; |
| see [RoboCasa](https://robocasa.ai/) for its attribution and upstream terms. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{sridhar2026barx, |
| title = {Cross-Embodiment Transfer via Behavior-Aligned Representations}, |
| author = {Sridhar, Ajay and Gao, Jensen and Yang, Jonathan and Mercat, Jean and Belkhale, Suneel and Sadigh, Dorsa}, |
| booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, |
| year = {2026} |
| } |
| ``` |
|
|
| Please also cite RoboCasa and MimicGen when using the corresponding simulator |
| assets or generated subset. |
|
|
