Rui Guo

Shanghai Tunnel Engineering Rail Transit Design & Research Institute, Nankai University, Xi'an Jiaotong University

Papers

Total Citations

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About

Rui Guo is a researcher specializing in robotics, 3D mapping, and simultaneous localization and mapping (SLAM), with a particular focus on advancing algorithms for environmental perception and point cloud registration. Their work spans over a decade, reflecting a sustained commitment to solving fundamental challenges in autonomous systems and spatial data processing. Guo's early contributions include the development of a simulation framework for active SLAM using Extended Kalman Filter (EKF), a foundational approach that helped validate algorithm performance in robotics navigation — a paper that has garnered 20 citations. Building on this foundation, their research evolved toward sophisticated multi-view scan registration techniques, introducing weighted motion averaging methods (19 citations) and hierarchical K-means clustering approaches (17 citations) that improve the accuracy and efficiency of aligning complex 3D point sets. Their 2019 work on outdoor environment mapping through scan matching and motion averaging, earning 21 citations, represents a significant practical contribution to autonomous navigation in real-world settings. Collectively, Guo's research has accumulated over 75 citations, demonstrating meaningful influence within the robotics and computer vision communities. Students working in autonomous navigation, LiDAR-based mapping, or point cloud processing will find Guo's methodological contributions particularly relevant and instructive.