e-Rshad: Enabling Inclusive Indoor Navigation for Individuals with Visual Impairments (CMUQ - Seed)
Eduardo Feo Flushing (LPI), Khaled Harras, Mai Al-Mashhadani, Yaqoob Ansari, Gustavo Ramalho
This project aims to develop e-Rshad, a conversational and adaptive navigation system designed for individuals with visual impairments. Its purpose is to enhance their navigation experience in complex public spaces such as shopping malls, museums, and airports. Traditional navigation tools often fall short in these areas due to their high cost, limited availability, and reliance on privacy-compromising cameras. This proposal aims to bridge these gaps by using alternative privacy-preserving sensor modalities like low-cost mmWave radar and low-resolution thermal sensors, along with recent advances in AI, to ensure reliable navigation. The project will also create comprehensive datasets tailored to assistive navigation, leading to advancements in the field. The contributions of this project will empower individuals with visual impairments, fostering their independence and improving their quality of life through a more accessible, privacy-aware indoor navigation solution.

Related Publications

 

Towards Practical and Deployable Infrastructure-Free Indoor Localization

Mai Al-Mashhadani, Yaqoob Ansari, Eduardo Feo-Flushing, Khaled Harras
To appear in Proceedings of IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2026

 

Tesseract: Unfolding Navigable Graph Representations from Low-Semantic Floor Plans

Yaqoob Ansari, Ammar Karkour, Eduardo Feo-Flushing, Khaled A. Harras
Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL/GIS), 2025
PDF

 

A Deployable Privacy-Preserving Thermal-Based Obstacle Detection System for Indoor Navigation

Jingxiang Gao, Hend K. Gedawy, Eduardo Feo-Flushing, Khaled A. Harras
IEEE International Conference on Communications (ICC), 2025
PDF

 

Text2Map: From Navigational Instructions to Graph-Based Indoor Map Representations Using LLMs

Ammar Karkour, Khaled A. Harras, Eduardo Feo-Flushing
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
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