Jingkun Fan

Papers

Total Citations

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About

Jingkun Fan is a leading researcher in intelligent optimization algorithms and autonomous mobile robotics, with a particular focus on path planning and swarm intelligence. Their most influential work, "A multi-strategy improved sparrow search algorithm for mobile robots path planning" (2024, 17 citations), introduces a novel hybrid optimization framework that significantly enhances the efficiency and robustness of robot navigation in complex, obstacle-rich environments. By integrating multiple search strategies into the sparrow search algorithm, Fan’s approach addresses critical limitations in convergence speed and path quality, enabling mobile robots to generate feasible, collision-free trajectories with reduced computational cost. This contribution has direct implications for warehouse automation, search-and-rescue operations, and autonomous driving systems. Beyond this flagship paper, Fan’s broader research portfolio explores adaptive metaheuristics and real-time decision-making for robotic systems. Their work is characterized by a practical, application-driven methodology that bridges theoretical algorithm design with tangible engineering solutions. With a growing citation record and a clear trajectory toward solving real-world mobility challenges, Jingkun Fan is establishing themselves as an emerging authority in the intersection of computational intelligence and robotics.