LLM-Glasses: GenAI-Driven Glasses with Haptic Feedback for Navigation of Visually Impaired People

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Authors: Issatay Tokmurziyev, Miguel Altamirano Cabrera, Muhammad Haris Khan, Yara Mahmoud, Dzmitry Tsetserukou
Cited by: 7
References: 17

Abstract

LLM-Glasses is a wearable navigation system which assists visually impaired people by utilizing YOLO-World object detection, GPT-4o-based reasoning, and haptic feedback for real-time guidance. The device translates visual scene understanding into intuitive tactile feedback on the temples, allowing hands-free navigation. Three studies evaluate the system: recognition of 13 haptic patterns with an average recognition rate of 81.3%, VICON-based guidance with predefined paths using haptic cues, and an LLM-guided scene evaluation with decision accuracies of 91.8% without obstacles, 84.6% with static obstacles, and 81.5% with dynamic obstacles. These results show that LLM-Glasses can deliver reliable navigation support in controlled environments and motivate further work on responsiveness and deployment in more complex real-world scenarios.

Fields of Study & Subjects

Tactile and Sensory Interactions Gaze Tracking and Assistive Technology Advanced Sensor and Energy Harvesting Materials

Publication details

Journal / source
Companion Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction
Publisher
ACM
Pages
994–998
Publication date
12 March 2026