Fuming Xie
Papers
1
Total Citations
2
H-Index
1
About
Fuming Xie is a researcher at the forefront of agricultural robotics and autonomous navigation, specializing in robust localization solutions for complex, GNSS-challenged environments. His primary research areas encompass sensor fusion, simultaneous localization and mapping (SLAM), and the application of neural networks to enhance robotic perception in agricultural settings. Xie’s most notable contribution is his pioneering work on a neural network-based SLAM/GNSS fusion localization algorithm, designed to prevent the loss of control in agricultural robots operating in orchards and farmlands where GNSS signals are degraded or denied. This work, published in 2025 and already garnering 2 citations, addresses a critical bottleneck in precision agriculture: maintaining reliable robot navigation under dense tree canopies or in cluttered field conditions. By intelligently fusing SLAM data with intermittent GNSS readings, Xie’s approach significantly improves localization accuracy and system resilience. His research holds profound implications for the future of autonomous farming, enabling robots to perform tasks like spraying, harvesting, and monitoring with greater reliability. Xie’s work is essential reading for engineers and researchers developing field-deployable autonomous systems.
Research Focus
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Top Papers
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