Fuxiang Xie
Papers
4
Total Citations
54
H-Index
3
About
Fuxiang Xie is a leading researcher in agricultural robotics and intelligent automation, with a focus on developing autonomous systems for precision farming and industrial applications. His work centers on three key areas: robot navigation in complex environments, deep learning for fruit detection, and 3D modeling for agricultural management. Xie’s major contributions include pioneering a navigation method for orchard robots using point cloud maps, which enhances path planning in unstructured settings, and creating the Shine-Muscat Grape Detection Model (S-GDM) that improves green grape identification accuracy despite branch occlusion and cluster adhesion—a critical step for fruit-picking robots. He also developed a robotic platform with LiDAR-based algorithms for canopy volume measurement of fruit trees, enabling precise agricultural assessments. With over 50 citations across his most-cited papers, including 22 for his 2024 orchard navigation study, Xie’s work has significant impact. Notably, his design of a vacuum system for a large storage tank cleaning robot showcases his versatility, integrating simulation tools like Fluent-EDEM for optimization. Xie’s innovations advance both agricultural robotics and industrial automation, offering practical solutions for real-world challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2A study on Shine-Muscat grape detection at maturity based on deep learning16 citations · 2023
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