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---

license: apache-2.0
---

# XR-1-Dataset-Sample

[[Project Page](https://github.com/Open-X-Humanoid/XR-1)] [[Paper](https://arxiv.org/abs/2411.02776v1)] [[GitHub](https://github.com/Open-X-Humanoid/XR-1)]

This repository contains a representative sample of the **XR-1** project's multi-modal dataset. The data is organized to support cross-embodiment training for Humanoids, Manipulators, and Ego-centric vision.

## πŸ“‚ Directory Structure

The dataset follows a hierarchy based on **Embodiment -> Task -> Format**:

### 1. Robot Embodiment Data (LeRobot Format)
Standard robot data (like TienKung or UR5) is organized following the [LeRobot](https://github.com/huggingface/lerobot) convention:

```text
XR-1-Dataset-Sample/
└── DUAL_ARM_TIEN_KUNG2/                      # Robot Embodiment
    └── Press_Green_Button/              # Task Name
        └── lerobot/               # Data in LeRobot format
            β”œβ”€β”€ metadata.json     
            β”œβ”€β”€ episodes.jsonl     
            β”œβ”€β”€ videos/            
            └── data/             

```

### 2. Human/Ego-centric Data (Ego4D Format)

For ego-centric data (e.g., Ego4D subsets used for Stage 1 UVMC pre-training), the structure is adapted to its native recording format:

```text
XR-1-Dataset-Sample/
└── Ego4D/                         # Human ego-centric source
    β”œβ”€β”€ files.json                 # Unified annotation/mapping file
    └── files/                     # Raw data storage
        └── [video_id].mp4         # Egocentric video clips
```

## πŸ€– Data Modalities

* **Vision**: High-frequency RGB streams from multiple camera perspectives.
* **Motion**: Continuous state-action pairs, which are tokenized into **UVMC** (Unified Vision-Motion Codes) for XR-1 training.
* **Language**: Natural language instructions paired with each episode for VLA alignment.

## πŸ›  Usage

This sample is intended for use with the [XR-1 GitHub Repository](https://github.com/Open-X-Humanoid/XR-1). 

## πŸ“ Citation

```bibtex
@article{fan2025xr,
  title={XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations},
  author={Fan, Shichao and others},
  journal={arXiv preprint arXiv:2411.02776},
  year={2025}
}

```

## πŸ“œ License

This dataset is released under the [MIT License](https://github.com/Open-X-Humanoid/XR-1/blob/main/LICENSE).

---

**Contact**: For questions, please open an issue on our [GitHub](https://github.com/Open-X-Humanoid/XR-1).