Baoxiang Zhang

China University of Geosciences (Beijing)

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About

Baoxiang Zhang is at the forefront of integrating Global Navigation Satellite System (GNSS) precise point positioning (PPP) with robotic state estimation, pioneering high-precision navigation for autonomous systems. His key research areas span multi-sensor fusion, factor graph optimization, and simultaneous localization and mapping (SLAM), with a specific focus on bridging the gap between GNSS positioning and robotics. Zhang’s major contribution lies in introducing factor graph optimization—a technique widely used in robotic SLAM—to PPP ambiguity resolution, enabling more robust and accurate GNSS-based state estimation. His 2024 paper on this topic has already garnered 44 citations, reflecting its immediate impact on the field. In his most recent work (2025), Zhang addresses the critical challenge of maintaining continuous positioning in complex environments by developing a loosely coupled PPP/Inertial/LiDAR SLAM system based on graph optimization. This work directly tackles the vulnerability of standalone PPP to signal interference, offering a solution for self-driving and mobile robot applications. By merging geodetic precision with robotic flexibility, Zhang is shaping the future of autonomous navigation.