Lin Meijin

Papers

Total Citations

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About

Dr. Lin Meijin is a researcher whose work centers on advancing intelligent robotics and optimization algorithms, with a particular focus on enhancing autonomous navigation and path planning. Their most cited paper, "Robot Path Planning Based on Improved Particle Swarm Optimization" (2021), introduces a novel hybrid approach that combines particle swarm optimization (PSO) with grey wolf optimization (GWO) to improve both the safety and efficiency of robot movement. By integrating chaotic random mechanisms, Dr. Lin’s method addresses critical challenges in real-time obstacle avoidance and route optimization, offering more robust solutions than traditional single-algorithm approaches. With 11 citations, this work has already gained recognition among peers working in swarm intelligence and mobile robotics. Dr. Lin’s contributions are especially valuable for applications in automated manufacturing, search-and-rescue operations, and autonomous vehicles, where reliable path planning is essential. Their research exemplifies a practical, interdisciplinary approach—bridging metaheuristic theory and robotic implementation—and continues to inspire further innovations in intelligent motion control and adaptive optimization.