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license: apache-2.0
task_categories:
- robotics
---
# XR-1-Dataset-Sample
[[Project Page](https://xr-1-vla.github.io/)] [[Paper](https://huggingface.co/papers/2511.02776)] [[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.
## 📂 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
├── metadata.json
├── episodes.jsonl
├── 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
├── files.json # Unified annotation/mapping file
└── files/ # Raw data storage
└── [video_id].mp4 # Egocentric video clips
```
## 🤖 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.
## 🛠 Usage
This sample is intended for use with the [XR-1 GitHub Repository](https://github.com/Open-X-Humanoid/XR-1).
## 📝 Citation
```bibtex
@inproceedings{fan2025xr,
title={XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations},
author={Fan, Shichao and Wu, Kun and Che, Zhengping and Wang, Xinhua and Wu, Di and Liao, Fei and Liu, Ning and Zhang, Yixue and Zhao, Zhen and Xu, Zhiyuan and others},
booktitle={Proceedings of the International Conference on Machine Learning (ICML)},
year={2026}
}
```
## 📜 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).
## Discussions
If you're interested in XR-1, welcome to join our WeChat group for discussions.
<img src="https://cdn-uploads.huggingface.co/production/uploads/6776382cba4c337914f956d5/njWmHwX71fhItDBh_4Qo4.png" border=0 width=30%> |