What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?
This paper investigates key factors affecting transfer from everyday internet videos to robot manipulation policies. Using a new dataset of 532 human videos with 28 hours of high-quality hand labels, the authors find that hand pose quality matters, but the inherent motion gap hinders transfer unless networks specialize to each embodiment. Their cotraining recipe yields a 29.7% absolute success rate gain in low-robot-data regimes across six tasks.
[2606.06627] What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?
[Submitted on 4 Jun 2026]
Title:What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?
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Abstract:Human video datasets used for cotraining robot manipulation policies largely consist of curated demonstrations where motions are orchestrated to resemble robot behavior and 3D hand poses are captured with specialized hardware. A more plentiful source of data is everyday Internet video, but it is an open question what factors enable transfer from such videos to robots. We investigate this using a new dataset of 532 human videos with 28 hours of high-quality triangulated hand labels and natural motions. We find that hand pose quality affects transfer, but even with accurate hands, the inherent motion gap hinders transfer unless the vision and policy networks specialize to each embodiment. Our cotraining recipe yields consistent improvements, with an absolute success rate gain of $29.7\%$ in the low-robot-data regime across six manipulation tasks.
Comments: The project website is here: this https URL
Subjects:
Robotics (cs.RO); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
Cite as: arXiv:2606.06627 [cs.RO]
(or arXiv:2606.06627v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2606.06627
arXiv-issued DOI via DataCite (pending registration)
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From: Richard Li [view email] [v1] Thu, 4 Jun 2026 18:24:23 UTC (34,020 KB)
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