Papers
1
Total Citations
3
H-Index
1
About
Lihong Wan is a leading researcher in agricultural robotics and intelligent sensing, with a primary focus on overcoming the challenges of indoor localization in complex agricultural environments. Her most significant contribution is the development of an innovative indoor localization method that integrates Non-Line-of-Sight (NLOS) base station identification with an Improved Black Kite Algorithm–Backpropagation (IBKA-BP) neural network. This work directly addresses the critical problem of low positioning accuracy for robots operating in GPS-denied settings like greenhouses and breeding facilities. Her 2025 paper on this topic has already garnered 3 citations, signaling its immediate relevance to the field. Wan’s research is pivotal for advancing precision agriculture, enabling autonomous robots to navigate reliably in cluttered, signal-obstructed spaces. By fusing robust base station filtering with a novel optimization algorithm, she has provided a practical solution that enhances the operational efficiency of agricultural robots. Her work stands out for its direct application to real-world farming challenges, making her a key figure in the intersection of robotics, sensor fusion, and smart agriculture.
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