Uranus
Collection
4 items β’ Updated β’ 1
Download and unpack the samples from either Hugging Face or ModelScope into examples/data/.
pip install -U huggingface_hub
hf download D-Robotics/Uranus-Demo-Data \
--repo-type dataset \
--local-dir ./examples/data
pip install -U modelscope
modelscope download \
--dataset D-Robotics/Uranus-Demo-Data \
--local_dir ./examples/data
Each episode lands in ./examples/data/<episode_id>/ and can be passed directly to main.py --sample-dir.
Each sample is a self-contained "XML-environment" directory:
sample_dir/
βββ meta.json # prompt, cameras, mjcf_path, end_effectors, skeleton, fps
βββ temporal.json # step_qpos: [{state, robot2world_transform}, ...]
βββ mjcf/
β βββ <robot>.xml # robot MJCF with baked-in camera calibration & mounts
βββ ref_images/
β βββ <camera>.png # one reference image per camera
βββ gt/
βββ <camera>.mp4 # ground-truth video per camera
Your own robot data can be converted into this same format and fed to inference as well, as long as it provides the per-frame qpos, the robot MJCF with calibrated cameras, and one reference image per camera.
The Apache-2.0 license declared for this repository applies only to the original code and materials released by this project. Samples derived from third-party datasets remain subject to their respective upstream licenses and terms of use.
| Source dataset | License | Source |
|---|---|---|
| AgiBot World 2026 | CC BY-NC-SA 4.0 | Dataset page |
| AgiBot World Beta | CC BY-NC-SA 4.0 | Dataset page |
| DROID | Apache License 2.0 | Dataset website |
| RoboChallenge Table30 | - | Dataset page |
| RoboChallenge Table30 v2 | - | Dataset page |