Fengying Xie
Papers
1
Total Citations
3
H-Index
1
About
Fengying Xie is a researcher advancing autonomous navigation in challenging agricultural environments. Her work focuses on the fusion of sensor technologies—specifically integrating Simultaneous Localization and Mapping (SLAM) with Global Navigation Satellite Systems (GNSS)—to ensure reliable robot control in GNSS-degraded or denied settings like dense orchards and complex farmlands. Her most-cited paper, “Neural Network-Based SLAM/GNSS Fusion Localization Algorithm for Agricultural Robots in Orchard GNSS-Degraded or Denied Environments” (2025), proposes a tightly-coupled lidar-inertial odometry framework enhanced by neural networks, addressing the critical problem of robot loss of control due to signal loss. This innovative approach has already garnered attention, accumulating 3 citations shortly after publication—a strong indicator of its relevance to the robotics and precision agriculture communities. Xie’s contributions are pivotal for enabling robust, real-time localization in environments where traditional GNSS fails, directly supporting the development of resilient agricultural robots. Her work stands at the intersection of robotics, sensor fusion, and deep learning, offering practical solutions for field automation.
Research Focus
Key Achievements
Top Papers
- 1