Xiaonan Guo
Papers
2
Total Citations
35
H-Index
2
About
Xiaonan Guo is a leading researcher in mobile robotics and intelligent navigation systems, with a focus on optimizing path planning for autonomous vehicles in complex environments. Her major contributions center on hybrid algorithmic approaches that combine evolutionary computation with classical search methods. In her most-cited work, "Mobile Robot Path Planning based on Improved Genetic Algorithm With A-star Heuristic Method" (2020, 31 citations), Guo pioneered a novel technique that integrates the evaluation function of the A* algorithm into a genetic algorithm framework, significantly enhancing search efficiency for mobile robot path planning in complicated grid-based maps. This work addresses a critical challenge in robotics—balancing computational speed with path optimality in real-world scenarios. Additionally, Guo's research on the "Field Environment Intelligent Navigation System for Tomato Transportation Robot Based on Dijkstra" (2019) demonstrates her commitment to practical agricultural applications, developing robust navigation solutions for autonomous fruit transport in unstructured field environments. Her work bridges theoretical algorithmic innovation with tangible robotic implementations, making her a notable figure in the intersection of computational intelligence and field robotics.
Research Focus
Key Achievements
Top Papers
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- 2