Jing Fu

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About

Dr. Jing Fu is a leading researcher in autonomous vehicle navigation, with a primary focus on simultaneous localization and mapping (SLAM) and sensor fusion. Their most influential work, "Lidar Scan matching EKF-SLAM using the differential model of vehicle motion" (2013, 31 citations), addresses a core challenge in achieving true vehicle intelligence: enabling a robot to simultaneously position itself and build a map of its environment. Dr. Fu advanced the widely-used Extended Kalman Filter (EKF)-SLAM algorithm by integrating a differential motion model with LiDAR scan matching, significantly improving localization accuracy and map consistency for mobile robots. This contribution has been foundational for researchers working on robust, real-time navigation systems. By refining how vehicles interpret sensor data and model their own dynamics, Dr. Fu has helped bridge the gap between theoretical SLAM methods and practical deployment in autonomous driving and robotics. Their work continues to influence the development of more reliable, self-localizing systems in complex, unstructured environments.