--- license: apache-2.0 language: - en tags: - robotics - manipulation - locomotion - whole-body-control - dexterous-hands - humanoid - lerobot - groot - unitree-g1 - brainco - imitation-learning - long-horizon - household task_categories: - robotics pretty_name: G1 BrainCo WBT GR00T Dataset size_categories: - 100K/ ├── data/ │ └── chunk-000/ │ ├── episode_000000.parquet │ ├── episode_000001.parquet │ └── ... ├── videos/ │ └── chunk-000/ │ ├── observation.images.head_stereo_left_episode_000000.mp4 │ ├── observation.images.wrist_left_episode_000000.mp4 │ └── ... └── meta/ ├── modality.json ← GR00T-specific key mappings (manipulation) ├── modality_wbc.json ← GR00T-specific key mappings (WBC / loco-manipulation) ├── episodes.jsonl ├── tasks.jsonl ├── stats.json └── relative_stats.json ``` --- ## GR00T N1.7 Fine-tuning This dataset was used to fine-tune [GR00T N1.7](https://github.com/NVIDIA/Isaac-GR00T) with three runs: | Run | Checkpoint | Action Space | Purpose | |-----|-----------|-------------|---------| | Run 1 | `nvidia/GR00T-N1.7-DROID` | 24D (arms + hands) | Manipulation — DROID init | | Run 2 | `nvidia/GR00T-N1.7-3B` | 60D (arms + hands + full body) | Loco-manipulation (WBC) | | Run 3 | `nvidia/GR00T-N1.7-3B` | 24D (arms + hands) | Manipulation — base init (baseline) | ### Quick start (manipulation) ```bash git clone https://github.com/NVIDIA/Isaac-GR00T cd Isaac-GR00T uv sync --all-extras bash examples/G1_Brainco/finetune_g1_brainco.sh \ --base-model-path nvidia/GR00T-N1.7-DROID \ --dataset-path dataset_g1/brainco/G1_WBT_Brainco_Collect_Plates_Into_Dishwasher:... \ --output-dir outputs/g1_brainco ``` ### Memory requirements (RTX 5090 / 32 GB) ```bash # Required flags for 32 GB VRAM: --gradient_checkpointing --optim paged_adamw_8bit --global_batch_size 1 --gradient_accumulation_steps 64 # Peak VRAM: ~26.5 GB ``` > **Important:** Always pass `--action-horizon 16` at eval/deployment. > The DROID config defaults to 40 steps; without this flag the server outputs wrong chunk sizes. --- ## Dataset Statistics | Task | Min | Median | Max | Std% | |------|-----|--------|-----|------| | Collect Plates | 19.5s | 43.3s | 124.3s | 30% | | Make the Bed | 12.6s | 21.7s | 46.1s | 29% | | Pick Up Medicine | 13.3s | 24.2s | 56.1s | 30% | | Pickup Pillow | 12.3s | 18.9s | 37.2s | 23% | All episodes: zero NaNs, `hand_cmd` range [0.0, 0.8], `ee_action` within ±π. --- ## Related Dataset For single-object pick & grasp tasks (8 tasks, 1598 episodes, direct joint-space actions): 👉 [JeffrinSam/G1-BrainCo-Pick-GR00T](https://huggingface.co/datasets/JeffrinSam/G1-BrainCo-Pick-GR00T) --- ## Citation ```bibtex @dataset{unifolm_wbt_brainco_g1, title = {G1-BrainCo-GR00T-Dataset}, author = {JeffrinSam}, year = {2026}, note = {Unitree G1 + BrainCo dexterous hands manipulation dataset in LeRobot v2.1 format, prepared for GR00T N1.7 fine-tuning}, url = {https://huggingface.co/datasets/JeffrinSam/G1-BrainCo-GR00T-Dataset} } ``` --- ## License Data collected from [UnifoLM WBT Dataset](https://huggingface.co/collections/unitreerobotics/unifolm-wbt-dataset) by Unitree Robotics. Please refer to the original dataset license before commercial use.