Syed Abdullah Fadzli

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About

Syed Abdullah Fadzli is a robotics researcher whose work centers on indoor path planning and optimization algorithms for autonomous navigation. His primary research contributions focus on enhancing the efficiency of Dijkstra's algorithm—a foundational shortest-path method—by addressing its computational and storage limitations. In his most cited work, "Robotic Indoor Path Planning Using Dijkstra's Algorithm with Multi-Layer Dictionaries" (2015, 66 citations), Fadzli introduced an innovative data structure that replaces the conventional adjacency matrix with multi-layer dictionaries, significantly reducing storage overhead and enabling more scalable path planning in complex indoor environments. This contribution has been influential in the field of mobile robotics, providing a practical solution for real-time navigation. Additionally, his related paper on "Indoor Global Path Planning Based on Critical Cells Using Dijkstra Algorithm" (2015) further refines grid-based path planning by identifying critical cells to streamline route computation. With a total of 68 citations across his most-cited works, Fadzli’s research has provided valuable tools for roboticists and engineers developing autonomous systems for indoor settings, demonstrating how classic algorithms can be adapted for modern, resource-constrained applications.