SaiResearch/booster_dataset

Booster T1 Dataset

The Booster T1 Dataset is a collection of motion and control data capturing a humanoid robot (Booster T1) performing a diverse set of soccer-related actions. These include skills necessary for robot soccer such as kicking, dribbling, and goal kicks.

This dataset is designed to support research in robot soccer, reinforcement learning, motion planning, imitation learning, and control of bipedal robots in dynamic, contact-rich environments.

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Dataset Details

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Uses

Direct Use

• Training reinforcement learning and imitation learning policies.
• Motion planning and control benchmarking for humanoid soccer.
• Studying dynamic skills like ball-kicking, goal-kicking, and repositioning.
• Curriculum learning: starting from balance and stepping, progressing to soccer maneuvers.

Out-of-Scope Use

• Human motion modeling or biomechanical studies (data is robot-specific).
• Applications outside robotics locomotion and soccer (e.g., medical or sensitive domains).
• Any use that attempts to infer personal, demographic, or identity-related data (not present in this dataset).

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Dataset Structure

Each .npz file contains the following arrays:

• qpos: Concatenated positions (root position, root orientation quaternion, and DOF positions).
• qvel: Concatenated velocities (linear velocity, angular velocity, and DOF velocities).
• xpos, xquat, cvel, subtree_com, site_xpos, site_xmat: Currently placeholder arrays (zeros) reserved for extended features such as body/site positions and COM.
• split_points: Start and end indices for trajectory segmentation.
• joint_names: Names of robot joints.
• frequency: Target control frequency of the recorded trajectory.
• njnt: Number of joints.
• jnt_type: Joint types (0 = root, 3 = hinge).
• body_names, site_names, metadata: Reserved metadata placeholders.
• body_* and site_* arrays: Empty placeholders for MuJoCo-style body/site information (position, orientation, weld IDs, etc.).

This structure allows loading trajectories directly into MuJoCo-compatible formats for playback or analysis.

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Dataset Creation

Curation Rationale

The dataset was created to provide a standardized benchmark of soccer-related skills for humanoid robots, facilitating progress in robotic soccer research.

Recommendations

• Use as a benchmark for policy learning rather than as a standalone dataset for generalization.
• Combine with simulated data augmentation for robustness.

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Citation

If you use this dataset, please cite as:

BibTeX

@dataset{arenax2025booster,
  title     = {Booster T1 Dataset},
  author    = {ArenaX Labs},
  year      = {2025},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/SaiResearch/booster_dataset}
}