Yanqin Xun
Papers
1
Total Citations
4
H-Index
1
About
Yanqin Xun is a researcher whose work lies at the intersection of swarm intelligence algorithms and robotic path planning, with a particular focus on optimizing autonomous navigation in static environments. Their most cited paper, "Ant colony based on cat swarm optimization and application in picking robot path planning" (2016, 4 citations), introduces a novel hybrid approach that combines ant colony optimization (ACO) with cat swarm optimization (CSO) to address key limitations in multi-objective path planning. Xun identified that traditional ACO suffers from long computation times and a tendency to become trapped in local optima. By integrating the CSO searching model, their work proposes a more efficient and robust algorithm for picking robots, enabling faster convergence and better path quality. This contribution is particularly valuable for agricultural robotics and industrial automation, where efficient navigation is critical. While their citation count is modest, the work demonstrates a creative synthesis of bio-inspired algorithms, offering a practical solution to a real-world engineering challenge. Xun’s research continues to inspire further exploration into hybrid swarm intelligence methods for autonomous systems.
Research Focus
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Top Papers
- 1