用AR+A*算法实现校园室内导航，路径计算快2-3倍。
A Reliable Indoor Navigation System for Humans Using AR-based Technique
- 基于Vuforia建模环境，用A*算法算最短路径。
- 相比Dijkstra，小空间下速度提升2-3倍，内存占用更低。
- 适合校园等固定场景，体验直观，动态路径可更新。
现有室内导航系统在校园和小型区域中不可靠，用户依赖混乱的静态标识或平面图。本文提出一种基于AR技术的导航方案，使用Vuforia Area Target进行环境建模，通过AI导航的NavMesh组件结合A*算法实现路径规划。相较于Dijkstra算法，A*在较小搜索空间下求解速度快2至3倍，且在高复杂度环境中内存占用更低、处理时间更短。相比传统GPS方式，该系统可实时处理并叠加AR指引，动态响应环境变化，显著提升导航准确率与用户体验。实验表明，融合AR与路径算法的方法在有限封闭空间中可行且可扩展，具备良好的用户友好性。但在大型或高度动态环境中，仍需优化NavMesh性能。
原文摘要 · Abstract (English)
Reliable navigation systems are not available indoors, such as in campuses and small areas. Users must depend on confusing, time-consuming static signage or floor maps. In this paper, an AR-based technique has been applied to campus and small-site navigation, where Vuforia Area Target is used for environment modeling. AI navigation's NavMesh component is used for navigation purposes, and the A* algorithm is used within this component for shortest path calculation. Compared to Dijkstra's algorithm, it can reach a solution about two to three times faster for smaller search spaces. In many cases, Dijkstra's algorithm has difficulty performing well in high-complexity environments where memory usage grows and processing times increase. Compared to older approaches such as GPS, real-time processing and AR overlays can be combined to provide intuitive directions for users while dynamically updating the path in response to environmental changes. Experimental results indicate significantly improved navigation accuracy, better user experience, and greater efficiency compared to traditional methods. These results show that AR technology integrated with existing pathfinding algorithms is feasible and scalable, making it a user-friendly solution for indoor navigation. Although highly effective in limited and defined indoor spaces, further optimization of NavMesh is required for large or highly dynamic environments.
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