| | --- |
| | license: apache-2.0 |
| | task_categories: |
| | - robotics |
| | tags: |
| | - LeRobot |
| | configs: |
| | - config_name: default |
| | data_files: data/*/*.parquet |
| | --- |
| | |
| | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). |
| | # Dataset Card for **Smol-LIBERO** |
| |
|
| | ## Dataset Summary |
| | Smol-LIBERO is a **compact version of the LIBERO benchmark**, built to make experimentation fast and accessible. |
| | At just **1.79 GB** (compared to ~34 GB for the full LIBERO), it contains fewer trajectories and cameras while keeping the same multimodal structure. |
| |
|
| | Each sample includes: |
| | - **Images** from two fixed cameras |
| | - **Two types of robot state** (end-effector pose + gripper, and full 7-DoF joint positions) |
| | - **Actions** (7-DoF joint commands) |
| |
|
| | This setup is especially useful for comparing **low-dimensional state inputs** with **high-dimensional visual inputs**, or combining them in multimodal training. |
| |
|
| | --- |
| |
|
| | ## Dataset Structure |
| |
|
| | ### Data Fields |
| | - **`observation.images.image`**: 256×256×3 RGB image (camera 1) |
| | - **`observation.images.image2`**: 256×256×3 RGB image (camera 2) |
| | - **`observation.state`** *(8 floats)*: end-effector Cartesian pose + gripper |
| | `[x, y, z, roll, pitch, yaw, gripper, gripper]` |
| | - **`observation.state.joint`** *(7 floats)*: full joint angles |
| | `[joint_1, …, joint_7]` |
| | - **`action`** *(7 floats)*: target joint commands |
| |
|
| | --- |
| |
|
| | ## Why is it smaller than LIBERO? |
| | - **Fewer trajectories/tasks** → subset of the full benchmark |
| | - **Only two camera views** → reduced visual redundancy |
| | - **Reduced total frames** → shorter episodes or lower FPS |
| |
|
| | That’s why Smol-LIBERO is **1.79 GB instead of 34 GB**. |
| |
|
| | --- |
| |
|
| | ## Intended Uses |
| | - Quick prototyping and debugging |
| | - Comparing joint-space vs. Cartesian state inputs |
| | - Training small VLA baselines before scaling to LIBERO |
| |
|
| | --- |
| |
|
| | ## Limitations |
| | - Smaller task and visual diversity compared to LIBERO |
| | - Only two fixed camera views |
| | - May not fully represent generalization behavior on larger benchmarks |
| |
|
| | ## Citation |
| |
|
| | **BibTeX:** |
| |
|
| | ```bibtex |
| | [More Information Needed] |
| | ``` |
