Year: 2025
Type: conference-paper
Abstract: 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.
Authors: Aishwarya Jadhav, Jeffery Cao, Abhishree Shetty, Urvashi Kumar, Aditi Sharma, Ben Sukboontip, Jayant Tamarapalli, Jingyi Zhang, Aniruddh Koul
Institutions: Carnegie Mellon University, Pinterest (United States)
Language: English
Subfield: Occupational Therapy
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
Funder: Carnegie Mellon University
OpenAlex ID: W4410823636