A Reliable Indoor Navigation System for Humans Using AR-based Technique

TL;DR

This paper presents an AR-based indoor navigation system using Vuforia and AI navigation with NavMesh and A* algorithm, offering faster, more accurate directions compared to traditional methods, suitable for small indoor spaces.

Contribution

The study introduces an integrated AR and AI navigation system utilizing NavMesh and A* for indoor environments, demonstrating improved speed and accuracy over existing approaches.

Findings

A* algorithm is 2-3 times faster than Dijkstra's in small spaces.

AR overlays enhance real-time navigation accuracy.

System outperforms traditional signage and GPS in indoor settings.

Abstract

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.