Paper
A Reliable Indoor Navigation System for Humans Using AR-based Technique
Authors
Vijay U. Rathod, Manav S. Sharma, Shambhavi Verma, Aadi Joshi, Sachin Aage, Sujal Shahane
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.
Metadata
Related papers
Vibe Coding XR: Accelerating AI + XR Prototyping with XR Blocks and Gemini
Ruofei Du, Benjamin Hersh, David Li, Nels Numan, Xun Qian, Yanhe Chen, Zhongy... • 2026-03-25
Comparing Developer and LLM Biases in Code Evaluation
Aditya Mittal, Ryan Shar, Zichu Wu, Shyam Agarwal, Tongshuang Wu, Chris Donah... • 2026-03-25
The Stochastic Gap: A Markovian Framework for Pre-Deployment Reliability and Oversight-Cost Auditing in Agentic Artificial Intelligence
Biplab Pal, Santanu Bhattacharya • 2026-03-25
Retrieval Improvements Do Not Guarantee Better Answers: A Study of RAG for AI Policy QA
Saahil Mathur, Ryan David Rittner, Vedant Ajit Thakur, Daniel Stuart Schiff, ... • 2026-03-25
MARCH: Multi-Agent Reinforced Self-Check for LLM Hallucination
Zhuo Li, Yupeng Zhang, Pengyu Cheng, Jiajun Song, Mengyu Zhou, Hao Li, Shujie... • 2026-03-25
Raw Data (Debug)
{
"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2602.23706v1</id>\n <title>A Reliable Indoor Navigation System for Humans Using AR-based Technique</title>\n <updated>2026-02-27T06:18:49Z</updated>\n <link href='https://arxiv.org/abs/2602.23706v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2602.23706v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>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.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='cs.RO'/>\n <category scheme='http://arxiv.org/schemas/atom' term='cs.CV'/>\n <published>2026-02-27T06:18:49Z</published>\n <arxiv:comment>6 pages, 6 figures, 2 tables, Presented at 7th International Conference on Advances in Science and Technology (ICAST 2024-25)</arxiv:comment>\n <arxiv:primary_category term='cs.RO'/>\n <author>\n <name>Vijay U. Rathod</name>\n </author>\n <author>\n <name>Manav S. Sharma</name>\n </author>\n <author>\n <name>Shambhavi Verma</name>\n </author>\n <author>\n <name>Aadi Joshi</name>\n </author>\n <author>\n <name>Sachin Aage</name>\n </author>\n <author>\n <name>Sujal Shahane</name>\n </author>\n </entry>"
}