Ahmed Abdulbaky

Papers

Total Citations

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About

Ahmed Abdulbaky is a researcher specializing in mobile robotics, with a particular focus on simultaneous localization and mapping (SLAM) algorithms for indoor navigation. His most-cited work, "Experimental Analysis of Gmapping SLAM Algorithm for Mobile Robot Indoor Navigation" (2024), provides a rigorous investigation into how a mobile robot’s linear and angular velocities affect mapping accuracy when using LiDAR-based SLAM. By systematically analyzing deviations in 2D map construction, Abdulbaky offers practical insights for optimizing robot performance in real-world environments—a contribution that has already garnered 3 citations shortly after publication. His research bridges the gap between theoretical SLAM frameworks and their experimental validation, making it highly relevant for students and engineers working on autonomous systems. Abdulbaky’s work underscores the importance of parameter tuning in robotic navigation, and his findings serve as a valuable reference for improving the reliability of indoor mobile robots. As his citation count grows, his experimental approach is poised to influence future developments in SLAM-based navigation.