oxe-augecc-by-4.0
berkeley_autolab_ur5_test
An augmented robot dataset containing 104 episodes across 9 different robot embodiments (Google Robot, Jaco, Kinova3, KUKA IIWA, Panda, Sawyer, WidowX, xArm7) with synchronized RGB imagery and proprioceptive state information at 5 FPS.
Downloads114
Episodes104
Why This Matters for Physical AI
This dataset enables cross-embodiment policy learning by providing robot-augmented trajectories that allow models trained on one robot platform to transfer knowledge to multiple different embodiments through consistent state and action representations.
Technical Profile
- Modalities
- rgbproprioception
- Robot Embodiments
- google_robotjacokinova3kuka_iiwapandasawyerwidowXxarm7
- Environment
- lab
- Episodes
- 104
- Data Format
- parquet
- Annotation Types
- language_instructions
- License
- cc-by-4.0
Access
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