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README.md
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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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{"task_index": 0, "task": "put the white mug on the left plate and put the yellow and white mug on the right plate"}
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|
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{"task_index": 9, "task": "pick up the book and place it in the back compartment of the caddy"}
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|
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{"task_index": 13, "task": "put the cream cheese in the bowl"}
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|
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|
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|
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|
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{"task_index": 26, "task": "pick up the salad dressing and place it in the basket"}
|
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|
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|
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{"task_index": 29, "task": "pick up the chocolate pudding and place it in the basket"}
|
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{"task_index": 30, "task": "pick up the black bowl next to the cookie box and place it on the plate"}
|
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{"task_index": 31, "task": "pick up the black bowl in the top drawer of the wooden cabinet and place it on the plate"}
|
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{"task_index": 32, "task": "pick up the black bowl on the ramekin and place it on the plate"}
|
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{"task_index": 33, "task": "pick up the black bowl on the stove and place it on the plate"}
|
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{"task_index": 34, "task": "pick up the black bowl between the plate and the ramekin and place it on the plate"}
|
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{"task_index": 35, "task": "pick up the black bowl on the cookie box and place it on the plate"}
|
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{"task_index": 36, "task": "pick up the black bowl next to the plate and place it on the plate"}
|
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{"task_index": 37, "task": "pick up the black bowl next to the ramekin and place it on the plate"}
|
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{"task_index": 38, "task": "pick up the black bowl from table center and place it on the plate"}
|
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{"task_index": 39, "task": "pick up the black bowl on the wooden cabinet and place it on the plate"}
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