Lulu Ying
Papers
1
Total Citations
41
H-Index
1
About
Lulu Ying is a prominent researcher in the fields of autonomous underwater vehicle (AUV) navigation and intelligent control systems. Her work focuses on advancing simultaneous localization and mapping (SLAM) algorithms, particularly through the integration of particle swarm optimization (PSO) to enhance the efficiency and accuracy of autonomous navigation. In her most-cited paper, "Autonomous navigation based on unscented-FastSLAM using particle swarm optimization for autonomous underwater vehicles" (2015), Ying introduced a novel approach that optimizes particle distribution in FastSLAM, significantly improving state estimation in complex underwater environments. This contribution has garnered 41 citations, reflecting its influence on robotics and marine engineering. Her research addresses critical challenges in AUV autonomy, such as reducing computational load while maintaining robust performance in noisy, dynamic settings. Ying's work is notable for bridging theoretical optimization techniques with practical deployment, making her a key figure in the development of next-generation autonomous systems for ocean exploration and surveillance.
Research Focus
Key Achievements
Top Papers
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