A ROS 2-Based Wearable Navigation Architecture for Visually Impaired Users Using ToF and GNSS: A Proposed System and Evaluation Framework

Author

Jibin B Mathew, Mohana Vel S, Manigandan E


Abstract

 Independent mobility remains a significant challenge for visually impaired individuals, particularly when transitioning between indoor and outdoor environments where the reliability of positioning technologies differs sharply. This paper presents a proposed wearable assistive navigation architecture that combines time-of-flight (ToF)-based indoor sensing with GNSS-based outdoor positioning, coordinated through a ROS 2 architecture distributed across smart glasses and a sensor-equipped smart shoe, with guidance delivered through an audio headset and shoe-mounted haptic motors. This is a conceptual, design-stage paper that presents the proposed system architecture, candidate hardware components, proposed ROS 2 node design, and a proposed evaluation framework for future assessment of localization accuracy, obstacle-detection performance, mode-transition reliability, and usability. No hardware has been fabricated and no experiments have been conducted at the time of writing; accordingly, this paper reports no quantitative results. All proposed measurements are intended for a future prototype-validation study. The primary contribution is a distributed ROS 2 architecture that integrates head-mounted ToF and visual sensing with shoe-mounted proximity, inertial, pressure, and haptic sensing to support context-aware indoor–outdoor navigation.



Keywords

assistive navigation; visual impairment; wearable computing; ToF sensing; GNSS; sensor fusion; ROS 2; haptic feedback



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References


[1] Asiedu Asante, B. K., & Imamura, H. (2026). Seamless indoor and outdoor navigation using IMU-GNSS sensor data fusion. Sensors, 26(7), 2215. https://doi.org/10.3390/s26072215

[2] Bouteraa, Y. (2021). Design and development of a wearable assistive device integrating a fuzzy decision support system for blind and visually impaired people. Micromachines, 12(9), 1082. https://doi.org/10.3390/mi12091082

[3] Busaeed, S., Katib, I., Albeshri, A., Corchado, J. M., Yigitcanlar, T., & Mehmood, R. (2022). LidSonic V2.0: A LiDAR and deep-learning-based green assistive edge device to enhance mobility for the visually impaired. Sensors, 22(19), 7435. https://doi.org/10.3390/s22197435

[4] Moram, V., Zahruddin, S., & Kumar, S. (2025). Multifunctional assistive smart glasses for visually impaired. SN Computer Science, 6(2), 173. https://doi.org/10.1007/s42979-025-03701-2

[5] Tokmurziyev, I., Altamirano Cabrera, M., Khan, M. H., Mahmoud, Y., & Tsetserukou, D. (2025). LLM-Glasses: GenAI-driven glasses with haptic feedback for navigation of visually impaired people. arXiv. https://arxiv.org/abs/2503.16475

[6] Dascal, M., Blaga, O., Padure, M., & Amariei, C. (2024). Usability of an AI-based independent pedestrian navigation device designed for blind people. European Journal of Public Health, 34(Suppl 3), ckae144.1185. https://doi.org/10.1093/eurpub/ckae144.1185

[7] Almomani, A., Alauthman, M., Malkawi, A., Shwaihet, H., Aldigide, B., Aldabeek, D., & Abu Hamoodeh, K. (2023). Smart shoes safety system for the blind people based on (IoT) technology. Computers, Materials & Continua, 76(1), 415–436. https://doi.org/10.32604/cmc.2023.036266

[8] Amballa, D. P. (2018). Haptic feedback-enabled smart shoes for visually impaired navigation assistance. Journal of Scientific and Engineering Research, 5(1), 266–270. https://doi.org/10.5281/zenodo.11667290.

 

 

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