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About

Abrar M. Alajlan is a robotics researcher whose work centers on autonomous mobile robot navigation, collision avoidance, and intelligent path planning systems. His research has made meaningful contributions to the challenge of enabling robots to operate safely and efficiently in complex, real-world environments — a problem of growing importance as autonomous systems become increasingly prevalent across industrial, medical, and consumer applications. Alajlan's most influential work explores multi-sensor fusion strategies, combining technologies such as GPS, cameras, infrared, and ultrasonic sensors to give mobile robots a richer, more reliable understanding of their surroundings. His 2016 paper on trajectory planning and collision avoidance has garnered 67 citations, while his sensor fusion navigation model from 2015 has accumulated 59 citations — together reflecting strong recognition within the robotics research community. His investigations into fuzzy logic integration further demonstrate his interest in intelligent, adaptive control systems capable of performing in both static and dynamic environments. A consistent theme throughout his body of work is energy efficiency and real-time performance, as evidenced by his 2017 study on optimal, energy-conscious path planning algorithms. Alajlan's research provides foundational insights for engineers and scientists developing next-generation autonomous systems where safety, precision, and resource efficiency are paramount.