CLARU
oxe-auge2025cc-by-4.0

utokyo_xarm_pick_and_place_train_augmented

An augmented dataset of pick-and-place trajectories from the University of Tokyo XArm platform, augmented across 9 robot embodiments including Google Robot, Jaco, Kinova3, KUKA IIWA, Franka Panda, Sawyer, UR5e, and WidowX using the OXE-AugE framework.

Downloads84
Episodes92

Why This Matters for Physical AI

This dataset enables cross-embodiment policy learning by augmenting real pick-and-place demonstrations across multiple robot platforms, advancing the ability to train generalizable manipulation policies.

Technical Profile

Modalities
rgbproprioception
Robot Embodiments
google_robotjacokinova3kuka_iiwapandasawyerur5ewidowX
Action Space
joint_positions
Environment
lab
Task Types
pick_and_place
Episodes
92
Data Format
LeRobot
Annotation Types
language_instructions
License
cc-by-4.0
Part of the OXE-AugE family

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