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--- |
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license: cc-by-4.0 |
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task_categories: |
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- robotics |
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tags: |
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- robotics |
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- manipulation |
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- libero |
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- vision-language-action |
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- multi-task |
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- converted |
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- lerobot |
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pretty_name: LIBERO Converted |
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size_categories: |
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- 100K<n<1M |
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--- |
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# LIBERO Dataset for LeRobot |
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This is the [LIBERO dataset](https://huggingface.co/datasets/physical-intelligence/libero), **preprocessed by the HuggingFace VLA team to fit the LeRobot framework**. |
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The dataset is structured for easy use in VLA (Vision-Language-Action) LeRobot training pipelines, so you can easily train and evaluate models without extra preprocessing. |
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## Dataset Description |
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LIBERO (Language-Integrated Benchmark for Evaluating Robot Manipulation) is a comprehensive benchmark for robot manipulation tasks with natural language instructions. This dataset combines four individual Libero datasets: **Libero-Spatial**, **Libero-Object**, **Libero-Goal** and **Libero-10**. All datasets were taken from the original sources and converted into LeRobot format. |
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- **Homepage**: https://libero-project.github.io |
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- **Paper**: https://arxiv.org/abs/2306.03310 |
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- **License**: CC-BY 4.0 |
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This converted version maintains all original functionality while providing standardized feature naming conventions. |
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### Details |
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- **Episodes**: 1,693 manipulation episodes |
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- **Tasks**: 40 unique manipulation tasks |
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- **Robot**: Franka Panda 7-DOF arm |
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- **Cameras**: Dual camera setup (main view + wrist camera) |
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- **Resolution**: 256×256 RGB images |
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- **Action Space**: 7-dimensional (6 joint velocities + gripper) |
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- **FPS**: 10 Hz |
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## Dataset Structure |
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### Features |
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| Feature | Type | Shape | Description | |
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|---------|------|-------|-------------| |
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| `observation.images.image` | Image | (256, 256, 3) | Main camera RGB view | |
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| `observation.images.image2` | Image | (256, 256, 3) | Wrist camera RGB view | |
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| `observation.state` | Tensor | (8,) | Joint positions + gripper state | |
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| `action` | Tensor | (7,) | Target joint velocities + gripper action | |
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| `timestamp` | Float | () | Episode timestamp | |
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| `frame_index` | Int | () | Frame index within episode | |
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| `episode_index` | Int | () | Episode identifier | |
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| `index` | Int | () | Global frame index | |
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| `task_index` | Int | () | Task identifier (0-39) | |
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### Task Categories |
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The dataset includes 40 diverse manipulation tasks across multiple categories: |
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- **Pick and Place**: Object manipulation and placement |
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- **Drawer Operations**: Opening and closing drawers |
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- **Door Operations**: Handle manipulation and door opening/closing |
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- **Assembly Tasks**: Multi-object coordination and assembly |
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- **Tool Use**: Utilizing tools for manipulation tasks |
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## Usage |
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### Loading the Dataset |
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```python |
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from lerobot.datasets.lerobot_dataset import LeRobotDataset |
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# Load the converted dataset |
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dataset = LeRobotDataset("HuggingFaceVLA/libero") |
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# Access a sample |
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sample = dataset[0] |
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main_image = sample["observation.images.image"] |
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wrist_image = sample["observation.images.image2"] |
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robot_state = sample["observation.state"] |
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action = sample["action"] |
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``` |
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## Conversion Details |
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This dataset was converted from the original LIBERO v2.0 format to LeRobot v2.1 format with the following improvements: |
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1. **Standardized Feature Names**: Renamed keys to follow LeRobot conventions |
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2. **Added Episode Statistics**: Generated `episodes_stats.jsonl` for efficient loading |
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3. **Updated Metadata**: Compatible with latest LeRobot framework |
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4. **Structured Image Keys**: Organized image features under `observation.images.*` |
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5. **Preserved All Data**: No data loss during conversion |
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### Original to Converted Key Mapping |
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| Original Key | Converted Key | |
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|--------------|---------------| |
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| `image` | `observation.images.image` | |
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| `wrist_image` | `observation.images.image2` | |
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| `state` | `observation.state` | |
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| `actions` | `action` | |
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## Dataset Statistics |
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- **Total Episodes**: 1,693 |
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- **Total Frames**: 273,465 |
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- **Average Episode Length**: 161.6 frames |
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- **Dataset Size**: ~35GB |
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- **Format**: LeRobot v2.1 |
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## Citation |
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If you use this dataset, please cite the original LIBERO paper: |
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```bibtex |
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@article{liu2023libero, |
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title={LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning}, |
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author={Liu, Bo and Zeng, Yifeng and Patil, Arjun and Mu, Xingyu and Xu, Qingqing and Liu, Ying and Wu, Stone and Liu, Yurong and Tenenbaum, Joshua B and others}, |
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journal={arXiv preprint arXiv:2306.03310}, |
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year={2023} |
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} |
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``` |
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## License |
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This dataset is released under the CC-BY 4.0 License, following the original LIBERO dataset licensing. |
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## Original Dataset |
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- **Original Source**: [physical-intelligence/libero](https://huggingface.co/datasets/physical-intelligence/libero) |
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- **Paper**: [LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning](https://arxiv.org/abs/2306.03310) |
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- **Homepage**: [https://libero-project.github.io](https://libero-project.github.io) |
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## Conversion Process |
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This dataset was converted using the LeRobot conversion pipeline: |
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1. Downloaded original dataset from HuggingFace Hub |
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2. Applied LeRobot v2.0 to v2.1 conversion |
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3. Renamed features to standard conventions |
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4. Generated episode statistics |
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5. Validated data integrity |
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6. Uploaded with proper metadata |
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For questions about the conversion or issues with the dataset, please open an issue on the [LeRobot repository](https://github.com/huggingface/lerobot). |
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