Elia Nadira Sabudin

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About

Elia Nadira Sabudin is a robotics researcher whose work focuses on advancing autonomous navigation through innovative path planning algorithms. Her primary research areas include unmanned air vehicle (UAV) trajectory optimization, artificial potential field methods, and computational path efficiency for mobile robots. Sabudin’s major contributions center on improving the safety and reliability of robot navigation—most notably through her development of an improved potential field method that incorporates path pruning to eliminate local minima and redundant trajectories. Her 2020 review on cell decomposition path planning for UAVs, which has garnered 39 citations, provides a comprehensive taxonomy of classical and modern approaches, establishing her as a thoughtful synthesizer in the field. Her subsequent papers, with 17 and 15 citations respectively, demonstrate a sustained focus on making artificial potential field algorithms more computationally efficient and complete. This body of work directly addresses the three essential criteria of path planning—path length, computational complexity, and completeness—offering practical solutions for real-world robotic missions. Sabudin’s research is particularly valuable for students and engineers seeking robust, low-cost navigation strategies for autonomous systems operating in complex environments.