MVP-Nav: Multi-layer Value Map Planner Navigator
Zero-shot Object Goal Navigation (ZSON) with RGB-only perception poses a fundamental challenge for embodied agents, as the absence of explicit depth information introduces severe physical uncertainty and semantic-physical misalignment. Existing approaches either rely on high-level semantic reasoning without geometric grounding or learn end-to-end policies that lack explicit physical constraints, often resulting in semantically plausible but physically unsafe behaviors. In this paper, we propose MVP-Nav, a physical-aware RGB-only navigation framework that aligns perception, planning, and contro
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- PossiblePossibly related (embedding) · 47%Learning Structured Reasoning via Tractable Trajectory Control - Apple Machine Learning Research →
- PossiblePossibly related (embedding) · 45%gaopengbin/cesium-mcp →
- PossiblePossibly related (embedding) · 49%Neural sampling from cognitive maps enables goal-directed imagination and planning →
