Wejdan Mohammed Alshehri

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About

Wejdan Mohammed Alshehri is a robotics researcher specializing in autonomous navigation and intelligent control systems. Her work focuses on developing efficient algorithms for maze-solving robots, with particular emphasis on enhancing wall-follower approaches to improve real-time obstacle avoidance and path optimization. Alshehri’s most-cited paper, “Autonomous Maze Solving Robotics: Algorithms and Systems” (2021, 23 citations), provides a comprehensive survey of navigation strategies, while her subsequent study, “An Autonomous Maze-Solving Robotic System Based on an Enhanced Wall-Follower Approach” (2023, 20 citations), introduces a refined methodology that enables robots to more reliably interpret their surroundings and navigate complex environments. Together, these contributions have garnered over 40 citations, reflecting their influence on the field of autonomous robotics. Alshehri’s work is particularly notable for bridging theoretical algorithm design with practical system implementation, addressing the fundamental challenge of enabling robots to autonomously discover paths from an initial point to a destination. Her research holds significant implications for applications in search-and-rescue, warehouse automation, and educational robotics, establishing her as a promising voice in the advancement of intelligent, self-navigating systems.