用小模型+A*算法，让室内导航无需信号也能实时生成清晰路线
Grid2Guide: A* Enabled Small Language Model for Indoor Navigation
- 结合A*路径规划与小语言模型生成可读指令
- 在多个场景中实现准确及时的导航引导
- 适合无定位信号的轻量级室内导航应用
可靠室内导航在缺乏外部定位信号和专用基础设施的复杂环境中仍是重大挑战。本文提出Grid2Guide，一种融合A*搜索算法与小型语言模型（SLM）的混合导航框架，用于生成清晰、人类可读的路径指引。该框架首先从给定室内地图构建二值占用矩阵，利用A*算法计算起点到终点的最优路径，并生成简洁的文本导航步骤；这些步骤再经由SLM转换为自然语言指令，提升终端用户的可理解性。在多种室内场景下的实验评估表明，该方法能有效生成准确且及时的导航指导。结果验证了所提方案作为轻量化、无需基础设施的实时室内导航支持系统的可行性。
原文摘要 · Abstract (English)
Reliable indoor navigation remains a significant challenge in complex environments, particularly where external positioning signals and dedicated infrastructures are unavailable. This research presents Grid2Guide, a hybrid navigation framework that combines the A* search algorithm with a Small Language Model (SLM) to generate clear, human-readable route instructions. The framework first conducts a binary occupancy matrix from a given indoor map. Using this matrix, the A* algorithm computes the optimal path between origin and destination, producing concise textual navigation steps. These steps are then transformed into natural language instructions by the SLM, enhancing interpretability for end users. Experimental evaluations across various indoor scenarios demonstrate the method's effectiveness in producing accurate and timely navigation guidance. The results validate the proposed approach as a lightweight, infrastructure-free solution for real-time indoor navigation support.
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