Papers
3
Total Citations
100
H-Index
3
About
Yanna Si is a researcher specializing in mobile robot path planning, with a focus on developing intelligent, adaptive algorithms for navigation in complex environments. Her major contributions lie in enhancing ant colony optimization (ACO) and rapidly-exploring random tree (RRT) methods to improve path efficiency, smoothness, and computational performance. In her most cited work, "An Adaptive Improved Ant Colony System Based on Population Information Entropy for Path Planning of Mobile Robot" (2021, 70 citations), Si introduced a novel approach that uses population information entropy to dynamically adjust algorithm parameters, significantly boosting optimization capability. She further advanced the field with "Path planning for mobile robot using an enhanced ant colony optimization and path geometric optimization" (2021, 27 citations), which combines an enhanced ACO with local geometric optimization for superior path quality. Her earlier work on smooth path planning using adaptive RRT (2018) laid groundwork for handling both simple and complex environments. With over 100 total citations, Si's research is widely recognized for its practical impact on autonomous navigation systems, making her a notable contributor to robotics and artificial intelligence.
Research Focus
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