ReMemNav improves zero-shot object navigation success and efficiency by integrating episodic memory and rethinking with VLMs, achieving SR/SPL gains of 1.7%/7.0% on HM3D v0.1, 18.2%/11.1% on HM3D v0.2, and 8.7%/7.9% on MP3D.
Openfmnav: Towards open-set zero-shot object navigation via vision-language foundation models,
3 Pith papers cite this work. Polarity classification is still indexing.
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cs.RO 3years
2026 3representative citing papers
A map-free localization method stores posed RGB-D keyframes, retrieves and re-ranks them with a VLM, then fuses sparse depth for on-demand 3D target estimates, matching reconstruction-based performance on navigation benchmarks with far lower build cost.
Introduces a hierarchical VLN architecture with asynchronous layers, incremental memory graph, and WTRP-based exploration that improves success and efficiency on resource-constrained robots.
citing papers explorer
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ReMemNav: A Rethinking and Memory-Augmented Framework for Zero-Shot Object Navigation
ReMemNav improves zero-shot object navigation success and efficiency by integrating episodic memory and rethinking with VLMs, achieving SR/SPL gains of 1.7%/7.0% on HM3D v0.1, 18.2%/11.1% on HM3D v0.2, and 8.7%/7.9% on MP3D.
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Memory Over Maps: 3D Object Localization Without Reconstruction
A map-free localization method stores posed RGB-D keyframes, retrieves and re-ranks them with a VLM, then fuses sparse depth for on-demand 3D target estimates, matching reconstruction-based performance on navigation benchmarks with far lower build cost.
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A Deployable Embodied Vision-Language Navigation System with Hierarchical Cognition and Context-Aware Exploration
Introduces a hierarchical VLN architecture with asynchronous layers, incremental memory graph, and WTRP-based exploration that improves success and efficiency on resource-constrained robots.