Rawnaq Adnan Mahmod

Papers

Total Citations

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About

Rawnaq Adnan Mahmod is a researcher specializing in sensor optimization, robotics, and intelligent algorithms, with a focused contribution to the field of embedded systems and autonomous applications. His most notable work centers on enhancing the performance of low-cost ultrasonic sensors for robotic applications, demonstrating a practical and innovative approach to solving real-world measurement challenges. In his highly cited 2023 paper, "Measurement Enhancement of Ultrasonic Sensor using Pelican Optimization Algorithm for Robotic Application," Mahmod applied the Pelican Optimization Algorithm to significantly improve the accuracy and reliability of the widely used HC-SR04 ultrasonic sensor, which measures distances ranging from 2 to 400 cm using reflected sound waves converted into electronic signals. This work, which has garnered 22 citations, bridges the gap between metaheuristic optimization techniques and practical robotic sensing, making advanced sensor calibration more accessible and cost-effective. Mahmod's research reflects a broader commitment to advancing intelligent robotic systems through algorithmic innovation, offering valuable insights for engineers and researchers working on autonomous navigation, distance measurement, and embedded sensor technologies. His contributions continue to influence the growing field of smart robotics and optimization-driven engineering solutions.