MapNav uses annotated semantic maps as memory for VLN agents, claiming SOTA results in simulation and real-world tests while promising code and data release.
Multi-floor zero-shot object navigation policy
3 Pith papers cite this work. Polarity classification is still indexing.
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EvolveNav adds an agentic rule memory with UCB retrieval and a memory-guided preflection module to enable continuous improvement in zero-shot object goal navigation, reporting a 10.1% success rate gain over baselines.
TravExplorer couples zero-shot semantic guidance with traversability-aware 3-D planning to enable cross-floor object navigation in unseen indoor environments.
citing papers explorer
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MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation
MapNav uses annotated semantic maps as memory for VLN agents, claiming SOTA results in simulation and real-world tests while promising code and data release.