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PoCo: Policy Composition from and for Heterogeneous Robot Learning

Training general robotic policies from heterogeneous data for different tasks is a significant challenge. Existing robotic datasets vary in different modalities such as color, depth, tactile, and proprioceptive information, and collected in different domains such as simulation, real robots, and human videos.

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Cite this as

Lirui Wang, Jialiang Zhao, Yilun Du, Edward H. Adelson, Russ Tedrake (2024). Dataset: PoCo: Policy Composition from and for Heterogeneous Robot Learning. https://doi.org/10.57702/brci8blw

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2402.02511
Author	Lirui Wang
More Authors	Jialiang Zhao Yilun Du Edward H. Adelson Russ Tedrake
Homepage	https://liruiw.github.io/policycomp