VTM-Nav: Hierarchical Visual-Topological Memory for Cross-Episode Object-Goal Navigation

Jul 17, 2026

Researchers introduce VTM-Nav, a training-free navigation framework that leverages a persistent hierarchical Visual-Topological Memory (VTM) to enable embodied agents to reuse experience across multiple episodes in the same environment. The VTM organizes scene knowledge at both room and object levels and retrieves relevant experience through a coarse-to-fine matching process. Evaluations on HM3D and MP3D benchmarks show that VTM-Nav outperforms a strengthened WMNav baseline, demonstrating improved performance and robustness in cross-episode object-goal navigation.

Why it matters: This work advances open-vocabulary navigation by enabling agents to effectively reuse experience without retraining, supporting more persistent and adaptable behavior in real-world environments.

Full story at: arXiv Computer Vision ↗