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arXiv · 2605.04327

From Language to Logic: A Theoretical Architecture for VLM-Grounded Safe Navigation

Kristy Sakano·Kalonji Harrington·Mumu Xu
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Abstract

We propose an architecture for integrating high-level, human-provided safety rules and operator-aligned semantic preferences into autonomous robot navigation in unstructured outdoor environments. In our approach, natural-language rules are translated into Signal Temporal Logic (STL) specifications that guide planning and navigation during runtime. Persistent, environment-centric rules and terrain preferences are grounded into a 2D cost map, while temporally dynamic requirements are expressed as STL specifications to be monitored during runtime. We hypothesize the use of Vision-Language Models (VLMs) for zero-shot scene understanding, enabling mapping between human instructions, semantic features, and environmental constraints. Within this framework, we construct an illustrative navigation model that is designed to satisfy a set of STL-encoded specifications and soft operator preferences through formal satisfaction metrics embedded into environmental properties and runtime monitoring.

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Kristy Sakano, Kalonji Harrington, Mumu Xu. 2026-05-05. From Language to Logic: A Theoretical Architecture for VLM-Grounded Safe Navigation. https://arxiv.org/abs/2605.04327

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