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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.

Data and Resources

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

DOI retrieved: December 16, 2024

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