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About

Kelin Tong is an emerging researcher specializing in autonomous mobile robotics, with a particular focus on intelligent path planning algorithms for agricultural environments. Their work sits at the intersection of computational intelligence and precision agriculture, addressing one of the most challenging problems in agricultural automation: enabling robots to navigate complex, dynamic greenhouse and orchard settings efficiently and safely. Tong's most significant contribution is the development of a hybrid approach combining an improved A* algorithm with fuzzy Dynamic Window Approach (DWA) logic for mobile robot navigation in greenhouse orchards, a paper that has rapidly accumulated 38 citations since its 2024 publication — a remarkable trajectory for work in this specialized domain. This research demonstrates Tong's ability to bridge classical path planning methods with modern fuzzy logic techniques to achieve practical, real-world performance. Building on this foundation, their 2025 work introduces a further hybrid framework integrating a modified Golden Jackal Optimization metaheuristic with dynamic window methods, reflecting a broader interest in nature-inspired computation applied to robotics. Though early in their career, Tong's focused and productive output signals strong potential for meaningful contributions to agricultural robotics and intelligent autonomous systems research.