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About

Semuil Tjiharjadi is a robotics researcher specializing in autonomous navigation and maze-solving algorithms, with a particular focus on pathfinding optimization for mobile robots. His work centers on the development and refinement of the Flood Fill algorithm, which he has systematically advanced through multiple implementations and comparative studies. Tjiharjadi’s most influential contribution is the design of a pathfinding robot using the Flood Fill algorithm, which has garnered 14 citations and established a foundation for subsequent research. He has further enhanced this approach by integrating the Flood Fill algorithm with A* search, Pledge navigation, and Wall Follower strategies, demonstrating measurable improvements in maze exploration efficiency. His 2022 paper on multi-agent pathfinding using an improved Flood Fill algorithm marks a significant step toward collaborative robotics. Collectively, his five most-cited papers have accumulated 37 citations, reflecting a steady impact in the niche field of algorithmic robot navigation. Tjiharjadi’s systematic, comparative methodology provides a valuable resource for students and researchers seeking to understand trade-offs between classic and hybrid pathfinding techniques in constrained environments.