MarvisNav: ゼロショット物体ナビゲーションにおける経路選択のための記憶の可視化
MarvisNav: Making Memory Visible on Route Choices for Zero-Shot Object Navigation
探索履歴を視覚的な経路候補に直接重ねて表示することで、VLMが目標関連性と探索状態を同時に評価できるゼロショット物体ナビゲーション手法を提案し、HM3Dで最高性能を達成した。
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著者: Jincheng Wang, Chi Pui Chan, Wei Zeng, Shuyang Zhang, Jianhao Jiao, Dimitrios Kanoulas
分類: cs.RO
原文アブストラクト
When searching for an object, people choose their next move by considering both likely target locations and places already explored. The current view can cue place-associated memories, bringing target relevance and prior exploration into the same spatial context. In many zero-shot object navigation (ZSON) methods, however, vision-language models (VLMs) infer promising search areas from egocentric images, while exploration history is represented separately, e.g., as text or maps. This separation either requires an additional fusion step or leaves the correspondence between memory and route choices implicit for the VLM to recover. We instead make exploration memory directly visible on visual route choices. We propose MarvisNav, a ZSON framework that maintains a topological graph and projects candidate nodes together with their exploration states onto egocentric views as memory-bearing visual route choices. These states capture local exploration progress beyond binary visitation. By binding exploration state directly to each visual candidate, MarvisNav enables the VLM to jointly evaluate target relevance and exploration state without a separate post-hoc fusion or reranking stage. Without policy training, MarvisNav achieves state-of-the-art performance on HM3D (81.2% SR and 42.5% SPL), while remaining competitive on MP3D. It also outperforms representative VLM-based methods with far fewer VLM calls (e.g., 7.5% of WMNav). Real-robot experiments across diverse scenes further validate its practical deployability. Beyond MarvisNav, our study shows that memory representation shapes VLM decisions and ZSON performance, highlighting that effective memory use depends not only on its availability, but also on how it is represented. Code and project page will be available at \url{https://wangjincheng1998.github.io/MarvisNav/}.