oxe-auge2025cc-by-4.0
berkeley_autolab_ur5_train_100_200
An augmented robotics dataset containing 100 episodes with multi-robot image augmentations across 9 different robot embodiments, featuring joint positions, end-effector poses, and natural language instructions.
Downloads94
Episodes100
Why This Matters for Physical AI
This dataset enables cross-embodiment policy learning by providing synchronized multi-robot augmentations of manipulation demonstrations, addressing the challenge of scaling robot learning across diverse hardware platforms.
Technical Profile
- Modalities
- rgbproprioceptionlanguage
- Robot Embodiments
- google_robotjacokinova3kuka_iiwapandasawyerwidowXxarm7
- Environment
- lab
- Task Types
- manipulation
- Episodes
- 100
- Data Format
- parquet
- Annotation Types
- language_instructions
- License
- cc-by-4.0
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