A framework decouples failure data for value estimation and success data for policy learning in offline RL to reduce collisions in robot navigation while maintaining success rates.
Offline reinforce- ment learning for visual navigation
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
FeudalNav decomposes visual navigation into hierarchical levels with a visual-similarity latent memory, delivering competitive Habitat AI results without any odometry.
citing papers explorer
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Learning from Demonstration with Failure Awareness for Safe Robot Navigation
A framework decouples failure data for value estimation and success data for policy learning in offline RL to reduce collisions in robot navigation while maintaining success rates.
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FeudalNav: A Simple Framework for Visual Navigation
FeudalNav decomposes visual navigation into hierarchical levels with a visual-similarity latent memory, delivering competitive Habitat AI results without any odometry.