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berkeley_autolab_ur5_train_600_700

An augmented robotics dataset containing 100 episodes with cross-embodiment visual and proprioceptive observations across 9 robot platforms, augmented from the Berkeley UR5 demonstration dataset.

Downloads171
Episodes100

Why This Matters for Physical AI

This dataset enables cross-embodiment policy learning by providing augmented visual and proprioceptive demonstrations across multiple robot platforms, advancing generalization of manipulation skills across different robot morphologies.

Technical Profile

Modalities
rgbproprioception
Robot Embodiments
google_robotjacokinova3kuka_iiwapandasawyerwidowXxarm7
Action Space
joint_positions
Environment
lab
Task Types
manipulation
Episodes
100
Data Format
parquet
Annotation Types
language_instructions
License
cc-by-4.0
Part of the OXE-Aug family

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