Xuemiao Xu

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About

Xuemiao Xu is a leading researcher in robotics and autonomous navigation, with a primary focus on simultaneous localization and mapping (SLAM) systems. Her major contributions center on advancing the robustness and accuracy of LiDAR-inertial SLAM, particularly through her work on adaptive global graph optimization techniques. This innovation addresses critical challenges in back-end optimization, ensuring that sensor data from LiDAR and inertial measurement units are fused more reliably to produce consistent maps and precise pose estimates, even in complex environments. Her most-cited paper, "Adaptive Global Graph Optimization for LiDAR-Inertial SLAM" (2024), has already garnered 4 citations shortly after publication, signaling its growing influence in the field. Xu’s research bridges the gap between front-end odometry and back-end optimization, offering practical solutions for autonomous systems like self-driving cars and mobile robots. Her work is notable for its focus on real-world deployment, making SLAM systems more adaptive and efficient. For students and researchers in robotics, Xuemiao Xu’s contributions represent a vital step toward fully autonomous navigation.