AI Guide Dog: Egocentric Path Prediction on Smartphone

Jadhav, Aishwarya, Cao, Jeffery, Shetty, Abhishree, Kumar, Urvashi Priyam, Sharma, Aditi, Sukboontip, Ben, Tamarapalli, Jayant Sravan, Zhang, Jingyi, Koul, Anirudh

arXiv.org Artificial Intelligence 

This paper introduces AI Guide Dog (AIGD), a lightweight egocentric navigation assistance system for visually impaired individuals, designed for real-time deployment on smartphones. AIGD addresses key challenges in blind navigation by employing a vision-only, multi-label classification approach to predict directional commands, ensuring safe traversal across diverse environments. We propose a novel technique to enable goal-based outdoor navigation by integrating GPS signals and high-level directions, while also addressing uncertain multi-path predictions for destination-free indoor navigation. Our generalized model is the first navigation assistance system to handle both goal-oriented and exploratory navigation scenarios across indoor and outdoor settings, establishing a new state-of-the-art in blind navigation. We present methods, datasets, evaluations, and deployment insights to encourage further innovations in assistive navigation systems.