Xuyou Li
Papers
3
Total Citations
88
H-Index
3
About
Xuyou Li’s research focuses on advancing autonomous mobile robotics, with key contributions in LiDAR-based simultaneous localization and mapping (SLAM), sensor fusion, and semantic scene understanding. His most-cited work, “Integrate Point-Cloud Segmentation with 3D LiDAR Scan-Matching for Mobile Robot Localization and Mapping” (2019, 62 citations), enhances the Iterative Closest Point (ICP) algorithm by incorporating point-cloud segmentation, significantly improving localization accuracy in complex environments. Building on this, his 2021 paper “LiDAR Odometry and Mapping Based on Semantic Information for Outdoor Environment” (20 citations) extends the popular LOAM framework by integrating semantic labels, enabling robust performance in dynamic outdoor settings. Li also introduced “Curvefusion” (2020, 6 citations), a novel method for combining estimated trajectories that addresses critical challenges in SLAM and time-calibration. His work directly impacts real-world applications, from autonomous navigation to exploration, by making LiDAR-based systems more reliable and efficient. With a growing citation record, Li is recognized for bridging geometric and semantic approaches in robotics, offering practical solutions that push the boundaries of mobile robot autonomy.
Research Focus
Key Achievements
Top Papers
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