This paper presents AI Guide Dog (AIGD), a lightweight egocentric (first-person) navigation system for visually impaired users, designed for real-time deployment on smartphones. AIGD employs a vision-only multi-label classification approach to predict directional commands, ensuring safe navigation across diverse environments. We introduce a novel technique for goal-based outdoor navigation by integrating GPS signals and high-level directions, while also handling uncertain multi-path predictions for destination-free indoor navigation. As the first navigation assistance system to handle both goal-oriented and exploratory navigation across indoor and outdoor settings, AIGD establishes a new benchmark in blind navigation. We present methods, datasets, evaluations, and deployment insights to encourage further innovations in assistive navigation systems.
@article{arxiv.2501.07957,
title = {AI Guide Dog: Egocentric Path Prediction on Smartphone},
author = {Aishwarya Jadhav and Jeffery Cao and Abhishree Shetty and Urvashi Priyam Kumar and Aditi Sharma and Ben Sukboontip and Jayant Sravan Tamarapalli and Jingyi Zhang and Anirudh Koul},
journal= {arXiv preprint arXiv:2501.07957},
year = {2025}
}
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Accepted at the AAAI 2025 Spring Symposium on Human-Compatible AI for Well-being: Harnessing Potential of GenAI for AI-Powered Science