Papers
4
Total Citations
13
H-Index
2
About
Xinlu Zong is a researcher focused on intelligent optimization algorithms and their applications in autonomous navigation, swarm intelligence, and pedestrian detection. Her work centers on developing bio-inspired and metaheuristic approaches to solve complex path planning and evacuation problems. Notably, she proposed a two-layer artificial fish swarm model that uses heterogeneous pheromones to simulate emergency evacuation in social networks, demonstrating how swarm behaviors like preying, swarming, and following can guide evacuees effectively. She also advanced mobile robot navigation by introducing a multi-strategy ensemble Harris hawks optimization algorithm (SDHHO), which achieves global optimal smooth path planning. Her research extends to pedestrian detection through channel feature fusion and enhanced semantic segmentation, as well as multi-objective unmanned vehicle path planning using whale optimization algorithms. With her most-cited paper garnering 6 citations, Zong’s contributions are steadily gaining recognition in the robotics and artificial intelligence communities. Her work is particularly valuable for students and researchers interested in how nature-inspired algorithms can be tailored to address real-world optimization challenges in autonomous systems and safety-critical applications.
Research Focus
Key Achievements
Top Papers
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