Mohammad Abedini

Babol Noshirvani University of Technology

Papers

Total Citations

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About

Mohammad Abedini has made impactful contributions to the field of robotics and autonomous navigation, with a primary focus on improving simultaneous localization and mapping (SLAM) estimation. His key research areas include trajectory tracking, positioning systems, and advanced filtering techniques for environments where GPS signals are unreliable or unavailable. Abedini’s most notable work, "Improved Simultaneous Localization and Mapping Estimation using Crow Search Algorithm Based Particle Filter" (2023), introduces a novel optimization approach that enhances the accuracy and robustness of SLAM by integrating a crow search algorithm with particle filtering. This contribution addresses critical challenges in autonomous vehicle and robot navigation, particularly in GPS-denied settings. While his citation count is still growing—with 2 citations for this paper—his research demonstrates strong potential for real-world applications in robotics and autonomous systems. Abedini’s work is especially relevant for students and researchers exploring intelligent algorithms for localization and mapping, as it bridges optimization theory with practical navigation solutions. His ongoing efforts promise to further advance the reliability of autonomous systems in complex environments.