Guorui Xiao

Papers

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About

Guorui Xiao is a leading researcher at the intersection of global navigation satellite systems (GNSS) and robotics, whose work is redefining high-precision state estimation. His primary research areas include precise point positioning (PPP), factor graph optimization, and multi-sensor fusion for simultaneous localization and mapping (SLAM). Xiao’s major contribution lies in pioneering the application of factor graph optimization—a technique proven in robotic SLAM—to GNSS positioning. His most cited work, "PPP based on factor graph optimization" (2024, 52 citations), demonstrates how this approach outperforms traditional Kalman filtering, reducing linearization errors and enabling more robust, real-time positioning. He further advanced the field by integrating PPP ambiguity resolution into the factor graph framework (44 citations), a critical step for achieving centimeter-level accuracy in dynamic environments. Most recently, his work on loosely coupled PPP/Inertial/LiDAR SLAM (2025) addresses the challenge of maintaining continuous, accurate navigation in signal-degraded conditions, a key enabler for autonomous driving and mobile robotics. With over 97 combined citations in just two years, Xiao’s research is quickly becoming foundational for next-generation, sensor-fusion-based navigation systems.