--- license: cc-by-nc-sa-4.0 language: - en - zh size_categories: - n>1T tags: - robotics - real-world - dual-arm - whole body control - manipulation - lerobot extra_gated_prompt: >- ### GALAXEA COMMUNITY LICENSE AGREEMENT: All the data and code within this repo are under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). extra_gated_fields: First Name: text Last Name: text Email: text Country: country Affiliation: text Phone: text Job title: type: select options: - Student - Research Graduate - AI researcher - AI developer/engineer - Reporter - Other geo: ip_location By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Galaxea Privacy Policy: checkbox extra_gated_description: >- The information you provide will be collected, stored, processed and shared in accordance with the Galaxea Privacy Policy. extra_gated_button_content: Submit --- # Galaxea Open-World Dataset [![Project Page](https://img.shields.io/badge/Project%20Page-000000?style=for-the-badge&logo=github)](https://opengalaxea.github.io/G0/) [![Paper](https://img.shields.io/badge/Paper-8A2BE2?style=for-the-badge&logo=arxiv)](https://arxiv.org/abs/2509.00576) [![Videos](https://img.shields.io/badge/Videos-FF0000?style=for-the-badge&logo=youtube)](https://opengalaxea.github.io/G0/) [![Visualizer](https://img.shields.io/badge/Visualizer-FF8C00?style=for-the-badge&logo=airplayvideo)](https://opengalaxea.github.io/G0/visualizer/index.html) [![Modelscope](https://img.shields.io/badge/Modelscope-1890FF?style=for-the-badge&logo=alibabacloud)](https://www.modelscope.cn/organization/Galaxea) [![Twitter](https://img.shields.io/badge/Twitter-FF6B35?style=for-the-badge&logo=x)](https://x.com/Galaxea_x) [![Linkedin](https://img.shields.io/badge/Linkedin-5865F2?style=for-the-badge&logo=linkedin)](https://www.linkedin.com/company/galaxeadynamics/posts/?feedView=all&viewAsMember=true) [![Discord](https://img.shields.io/badge/Discord-1890FF?style=for-the-badge&logo=discord)](https://discord.gg/hB6BuUWZZA) ## Key Features - **500+ hours** of real-world mobile manipulation data. - All data collected using **one uniform robotic embodiment** (R1-Lite) for consistency. - Fine-grained **subtask language annotations** (bilingual Chinese/English). - Covers **residential**, **kitchen**, **retail**, and **office** settings. - Dataset in **LeRobot v2.1** format. ## Dataset Structure The dataset is organized as **227 task-level tar.gz archives** under the `lerobot/` directory. Each archive contains a self-contained LeRobot dataset for one task: ``` lerobot/ ├── Adjust_The_Air_Conditioner_Temperature_20250711_006.tar.gz ├── Arrange_Fruits_20250819_011.tar.gz ├── Clean_The_Mirror_20250714_006.tar.gz ├── ... └── Wipe_The_Sewage_Stains_With_A_Ground_Cloth_20250801_012.tar.gz ``` After extracting a task archive, the directory follows the standard LeRobot v2.1 layout: ``` / ├── meta/ │ ├── info.json # Dataset metadata (features, fps, splits, etc.) │ ├── episodes.jsonl # Per-episode info (tasks, length, source file) │ └── episodes_stats.jsonl # Per-episode statistics ├── data/ │ └── chunk-000/ │ ├── episode_000000.parquet │ ├── episode_000001.parquet │ └── ... └── videos/ └── chunk-000/ ├── observation.images.head_rgb/ │ ├── episode_000000.mp4 │ └── ... ├── observation.images.head_right_rgb/ ├── observation.images.left_wrist_rgb/ └── observation.images.right_wrist_rgb/ ``` ## LeRobot Dataset Schema A detailed schema is available in [lerobot_info.json](https://huggingface.co/datasets/OpenGalaxea/Galaxea-Open-World-Dataset/blob/main/lerobot_info.json). Below is a summary of all features: ### Observations | Feature | Dtype | Shape | Description | |---|---|---|---| | `observation.images.head_rgb` | video | (720, 1280, 3) | Head camera RGB | | `observation.images.head_right_rgb` | video | (720, 1280, 3) | Head right camera RGB | | `observation.images.left_wrist_rgb` | video | (720, 1280, 3) | Left wrist camera RGB | | `observation.images.right_wrist_rgb` | video | (720, 1280, 3) | Right wrist camera RGB | | `observation.state.left_arm` | float64 | (6,) | Left arm joint positions | | `observation.state.left_arm.velocities` | float64 | (6,) | Left arm joint velocities | | `observation.state.right_arm` | float64 | (6,) | Right arm joint positions | | `observation.state.right_arm.velocities` | float64 | (6,) | Right arm joint velocities | | `observation.state.torso` | float64 | (4,) | Torso joint positions | | `observation.state.torso.velocities` | float64 | (4,) | Torso joint velocities | | `observation.state.chassis` | float64 | (3,) | Chassis positions | | `observation.state.chassis.velocities` | float64 | (3,) | Chassis velocities | | `observation.state.chassis.imu` | float64 | (10,) | Chassis IMU (orientation, angular velocity, linear acceleration) | | `observation.state.left_gripper` | float64 | (1,) | Left gripper state (0-close, 100-open) | | `observation.state.right_gripper` | float64 | (1,) | Right gripper state (0-close, 100-open) | | `observation.state.left_ee_pose` | float64 | (7,) | Left end-effector pose (position + quaternion) | | `observation.state.right_ee_pose` | float64 | (7,) | Right end-effector pose (position + quaternion) | ### Actions | Feature | Dtype | Shape | Description | |---|---|---|---| | `action.left_arm` | float64 | (6,) | Target left arm joint positions | | `action.right_arm` | float64 | (6,) | Target right arm joint positions | | `action.left_gripper` | float64 | (1,) | Target left gripper position | | `action.right_gripper` | float64 | (1,) | Target right gripper position | | `action.chassis.velocities` | float64 | (6,) | Target chassis twist (linear + angular) | | `action.torso.velocities` | float64 | (6,) | Target torso twist (linear + angular) | ### Metadata Columns | Feature | Dtype | Description | |---|---|---| | `timestamp` | float32 | Timestamp within episode | | `frame_index` | int64 | Frame index within episode | | `episode_index` | int64 | Episode index | | `index` | int64 | Global frame index | | `task_index` | int64 | Subtask annotation index | | `coarse_task_index` | int64 | Coarse-level task index | | `quality_index` | int64 | Quality annotation index | | `coarse_quality_index` | int64 | Coarse-level quality index | All video streams are encoded with **AV1 codec** at **15 fps**. ## Quick Start Below is an example of how to download and load a single task from the dataset using the Hugging Face Hub and LeRobot: ```python import tarfile from pathlib import Path from huggingface_hub import hf_hub_download from lerobot.common.datasets.lerobot_dataset import LeRobotDataset import torch # 1. Download a single task archive task_name = "Clean_The_Mirror_20250714_006" tar_path = hf_hub_download( repo_id="OpenGalaxea/Galaxea-Open-World-Dataset", filename=f"lerobot/{task_name}.tar.gz", repo_type="dataset", ) # 2. Extract it extract_dir = Path("./galaxea_data") extract_dir.mkdir(exist_ok=True) with tarfile.open(tar_path, "r:gz") as tar: tar.extractall(path=extract_dir) # 3. Load with LeRobot dataset = LeRobotDataset.from_local(str(extract_dir / task_name / task_name)) print(f"Number of episodes: {dataset.num_episodes}") print(f"Number of frames: {dataset.num_frames}") print(f"FPS: {dataset.fps}") # 4. Access a single frame frame = dataset[0] print(f"\nFrame keys: {list(frame.keys())}") print(f"Left arm state shape: {frame['observation.state.left_arm'].shape}") print(f"Left arm action shape: {frame['action.left_arm'].shape}") # 5. Iterate over an episode from torch.utils.data import DataLoader dataloader = DataLoader(dataset, batch_size=32, shuffle=False) for batch in dataloader: print(f"Batch observation.state.left_arm shape: {batch['observation.state.left_arm'].shape}") break ``` ## Citation All the data and code within this repo are under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). If you use our dataset or models, please cite: ```bibtex @article{galaxea2025, title={Galaxea G0: Open-World Dataset and Dual-System VLA Model}, author={Galaxea Team}, journal={arXiv preprint arXiv:2509.00576}, year={2025} } ```