Yiding Sun

Papers

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About

Yiding Sun is a leading researcher in multi-sensor integrated navigation systems, with a focus on autonomous mobile robotics and unmanned vehicles. His most cited work, "A Multi-Sensor Information Fusion Method Based on Factor Graph for Integrated Navigation System" (2021, 43 citations), addresses a critical challenge in autonomous navigation: efficiently fusing data from heterogeneous sensors that provide asynchronous measurements. Sun's key contribution lies in developing a factor graph-based fusion framework that overcomes the limitations of traditional filtering methods, enabling more accurate and robust state estimation for complex, real-time navigation tasks. This work has significant implications for the reliability of unmanned vehicles operating in dynamic environments. Beyond this paper, Sun's research spans sensor fusion algorithms, inertial navigation, and the integration of GPS, LiDAR, and visual odometry. His innovative approach to handling asynchronous data has been widely recognized, with his work serving as a foundational reference for engineers and researchers developing next-generation autonomous systems. Sun's contributions continue to drive advancements in safe and precise navigation for robotics and autonomous driving.