5 Humanoid LeRobot Datasets for VLA Training in 2026

A Voxel51 field guide examines five humanoid and bimanual manipulation datasets available in LeRobot v3.0 and FiftyOne, emphasizing “embodiment heterogeneity,” or the incompatibility created by robots’ differing kinematics, state and action spaces, camera configurations, and sensing modalities. The datasets span real-world AgiBot G2, Unitree G1, and Dexmate Vega-1 systems alongside simulated GR1T2 and Reachy2 humanoid torsos, with state vectors ranging from 29 dimensions for the Unitree G1 to 216 for AgiBotWorld2026, partly due to added reinforcement-learning collection signals. The paired TAVIS simulation datasets provide a controlled example, using identical tasks, cameras, and teleoperation procedures but differing in state size because the two robots have different degrees of freedom. HIW-500 records household teleoperation with a legged humanoid, AgiBotWorld includes human-intervened RL rollouts, and T-Rex adds extensive fingertip tactile sensing for dexterous bimanual manipulation. Because none share a unified state or action representation, they cannot be directly combined for cross-embodiment training without alignment approaches such as normalizing actions to shared end-effector representations, while licenses range from unrestricted MIT to non-commercial CC-BY-NC-SA.

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