AI RESEARCH
FeudalNav: A Simple Framework for Visual Navigation
arXiv CS.CV
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ArXi:2602.06974v2 Announce Type: replace-cross Visual navigation for robotics is inspired by the human ability to navigate environments using visual cues and memory, eliminating the need for detailed maps. In unseen, unmapped, or GPS-denied settings, traditional metric map-based methods fall short, prompting a shift toward learning-based approaches with minimal exploration. In this work, we develop a hierarchical framework that decomposes the navigation decision-making process into multiple levels.