Mourad Zghal

Centre d'Etudes Superieures Industrielles

Papers

Total Citations

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About

Mourad Zghal is a leading researcher in indoor robotics and multi-sensor data fusion, with a focus on enhancing autonomous robot localization in complex environments. His most cited work, "Double-Layer Soft Data Fusion for Indoor Robot WiFi-Visual Localization" (2025), introduces a pioneering method that integrates WiFi signal data with low-resolution visual inputs to achieve precise indoor positioning. This approach demonstrates remarkable efficiency, using only 10 WiFi samples and four 58×58 pixel images to localize a TIAGO++ robot with an average error of just 1.32 meters—a significant advancement for cost-effective, real-time navigation. Zghal’s contributions are particularly impactful for service robotics, smart buildings, and IoT applications, where reliable localization without expensive hardware is critical. With 4 citations already, this work underscores his ability to solve practical challenges in sensor fusion and robotic perception. His research continues to push boundaries in soft computing and data integration, offering scalable solutions for indoor autonomy that inspire both students and fellow researchers in the field.