Hybrid Vision Navigation with Hierarchical VLM–LLM Decision Making

This paper presents a hybrid navigation architecture for mapless navigation based on monocular vision. The system combines perception-driven affordance control with event-triggered semantic reasoning within a unified decision framework. Navigation behavior is governed by interpretable perceptual signals and a vision-derived progress proxy that enables self-monitoring. A reactive control regime ensures real-time safety, while a semantic reasoning module is activated only under persistent navigation difficulty to provide structured guidance. Experimental results in simulation and real-world deployment demonstrate improved success rate, safety, and efficiency compared to reactive and continuously active semantic baselines, while maintaining real-time performance on embedded hardware.