Xiaoyun Fan

Papers

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About

Xiaoyun Fan is a researcher specializing in autonomous navigation, mobile robotics, and LiDAR-based perception, with a particular focus on advancing simultaneous localization and mapping (SLAM) systems for unmanned ground vehicles (UGVs). Her most cited work, "2D LiDAR SLAM Back-End Optimization with Control Network Constraint for Mobile Mapping" (2018, 27 citations), makes a significant contribution by introducing a back-end optimization framework that integrates control network constraints to improve the accuracy and consistency of LiDAR SLAM in mobile mapping applications. This work addresses a critical challenge in robotics—enhancing SLAM robustness beyond traditional filtering approaches like Extended Kalman Filter (EKF)-based methods. Additionally, her paper "Real time UGV positioning based on Reference beacons aided LiDAR scan matching" (2018, 3 citations) demonstrates a practical, real-time positioning system that fuses IMU and 2D LiDAR data with reference beacons to achieve reliable localization in prepared environments. Fan’s research is notable for bridging theoretical SLAM optimization with real-world deployment, offering solutions that improve mapping precision for autonomous systems. Her work is valuable for students and researchers exploring LiDAR-based navigation, sensor fusion, and the practical implementation of SLAM in field robotics.