| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| dataset_info: |
| features: |
| - name: camera_images |
| list: image |
| - name: depth_images |
| list: image |
| - name: normal_images |
| list: image |
| - name: frame_id |
| dtype: int32 |
| - name: scene_id |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 3671744232.849 |
| num_examples: 1473 |
| download_size: 3336228908 |
| dataset_size: 3671744232.849 |
| --- |
| |
| # RoboTransfer-RealData |
|
|
| [**Project Page**](https://horizonrobotics.github.io/robot_lab/robotransfer) | [**Paper**](https://huggingface.co/papers/2505.23171) | [**GitHub**](https://github.com/HorizonRobotics/RoboTransfer) |
|
|
| RoboTransfer-RealData is a real-world robotic manipulation dataset collected using the ALOHA-AgileX robot system. It was introduced as part of the paper **"RoboTransfer: Controllable Geometry-Consistent Video Diffusion for Manipulation Policy Transfer"**. |
|
|
| The dataset contains real-world trajectories used to evaluate policy transfer from synthetic data generated by RoboTransfer, a diffusion-based framework designed for geometry-consistent robotic data synthesis. |
|
|
| ## Dataset Description |
|
|
| The dataset includes multi-modal visual data for robotic tasks: |
| - `camera_images`: RGB frames captured from the robot's camera system. |
| - `depth_images`: Corresponding depth maps for geometric conditioning. |
| - `normal_images`: Estimated surface normal maps. |
| - `frame_id`: The sequential index of the frame. |
| - `scene_id`: Identifier for specific recorded scenes. |
|
|
| ## Usage |
|
|
| As specified in the [RoboTransfer GitHub repository](https://github.com/HorizonRobotics/RoboTransfer), you can process raw RGB images from this dataset into the RoboTransfer format with geometric conditioning using the following script: |
|
|
| ```bash |
| script/process_real.sh |
| ``` |
|
|
| ## Citation |
|
|
| If you use this dataset or the RoboTransfer framework in your research, please cite: |
|
|
| ```bibtex |
| @misc{liu2025robotransfergeometryconsistentvideodiffusion, |
| title={RoboTransfer: Geometry-Consistent Video Diffusion for Robotic Visual Policy Transfer}, |
| author={Liu Liu and Xiaofeng Wang and Guosheng Zhao and Keyu Li and Wenkang Qin and Jiaxiong Qiu and Zheng Zhu and Guan Huang and Zhizhong Su}, |
| year={2025}, |
| eprint={2505.23171}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2505.23171}, |
| } |
| ``` |
