Haopeng Wei

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About

Haopeng Wei is at the forefront of integrating high-precision GNSS positioning with robotic state estimation, pioneering the application of factor graph optimization (FGO) to precise point positioning (PPP). While FGO has long been a staple in the SLAM community for camera, LiDAR, and inertial navigation, Wei’s work bridges a critical gap by introducing these advanced optimization techniques to GNSS-based positioning. His highly cited 2024 paper on "PPP based on factor graph optimization" (52 citations) demonstrates how FGO can outperform traditional Kalman filtering in reducing linearization errors and improving robustness. He further advanced this with "PPP ambiguity resolution based on factor graph optimization" (44 citations), enabling integer ambiguity resolution within the graph framework—a key step toward centimeter-level accuracy in challenging environments. Most recently, Wei extended this paradigm to multi-sensor fusion in "Loosely Coupled PPP/Inertial/LiDAR SLAM Based on Graph Optimization" (2025), addressing the vulnerability of PPP to signal interference in autonomous driving and mobile robotics. His work is instrumental in making high-precision GNSS a reliable component of modern SLAM systems, with direct applications in self-driving vehicles and autonomous navigation.