Xiongkui He
Papers
9
Total Citations
215
H-Index
5
About
Xiongkui He is a leading researcher in agricultural robotics and precision agriculture, with a focus on autonomous navigation, smart spraying systems, and robotic harvesting technologies for orchard and field environments. His most influential contributions center on developing intelligent unmanned ground vehicles capable of operating safely and efficiently in complex agricultural settings. His groundbreaking work on 3D LiDAR SLAM-based navigation systems for orchard spraying robots — garnering 87 citations since 2024 — has advanced the integration of NDT_ICP point cloud registration into real-world agricultural deployments. Complementing this, his research on precision variable-rate spraying robots using single 3D LiDAR systems (75 citations) has demonstrated practical pathways to reducing pesticide use while maintaining crop protection. He has also contributed significantly to smart harvesting through his comprehensive "Eye–Brain–Hand" framework review, which synthesizes advances in vision recognition, decision-making, and robotic manipulation. His more recent work explores deep learning for weed detection, monocular obstacle avoidance, and optimized grasping sequences using hybrid SOM-GA algorithms. Collectively, He's research bridges cutting-edge sensor fusion, machine learning, and robotics to address critical challenges in sustainable, automated agriculture.
Research Focus
Key Achievements
Top Papers
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- 2Precision Variable-Rate Spraying Robot by Using Single 3D LIDAR in Orchards75 citations · 2022
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