AI Guide Dog: Egocentric Path Prediction on Smartphone

Authors

  • Aishwarya Jadhav Carnegie Mellon University, Pittsburgh
  • Jeffery Cao Carnegie Mellon University, Pittsburgh
  • Abhishree Shetty Carnegie Mellon University, Pittsburgh
  • Urvashi Kumar Carnegie Mellon University, Pittsburgh
  • Aditi Sharma Carnegie Mellon University, Pittsburgh
  • Ben Sukboontip Carnegie Mellon University, Pittsburgh
  • Jayant Tamarapalli Carnegie Mellon University, Pittsburgh
  • Jingyi Zhang Carnegie Mellon University, Pittsburgh
  • Aniruddh Koul Pinterest

DOI:

https://doi.org/10.1609/aaaiss.v5i1.35591

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.

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Published

2025-05-28

How to Cite

Jadhav, A., Cao, J., Shetty, A., Kumar, U., Sharma, A., Sukboontip, B., … Koul, A. (2025). AI Guide Dog: Egocentric Path Prediction on Smartphone. Proceedings of the AAAI Symposium Series, 5(1), 220–227. https://doi.org/10.1609/aaaiss.v5i1.35591

Issue

Section

Human-Compatible AI for Well-being (Full Papers)