Self-Supervised Correspondence in Visuomotor Policy Learning
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DOI: 10.1109/lra.2019.2956365
Abstract: In this letter, we explore using self-supervised correspondence for improving the generalization performance and sample efficiency of visuomotor policy learning. Prior work has primarily used approaches such as autoencoding, pose-based losses, and end-to-end policy optimization… read more here.
Keywords: self supervised; policy learning; visuomotor; correspondence ... See more keywords