Daobin Wang

University of Science and Technology of China

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About

Daobin Wang is a leading researcher in mobile robotics, with key contributions in simultaneous localization and mapping (SLAM) and bio-inspired navigation. His work centers on developing robust, real-time positioning systems for autonomous vehicles and robots, particularly in GPS-denied environments. Wang’s most influential paper, “Lidar Scan matching EKF-SLAM using the differential model of vehicle motion” (2013, 31 citations), advances the widely used Extended Kalman Filter SLAM algorithm by integrating a differential motion model with lidar scan matching, significantly improving pose estimation accuracy for ground vehicles. He also pioneered the use of celestial cues for terrestrial navigation in “A camera-based real-time polarization sensor and its application to mobile robot navigation” (2014, 14 citations), creating a novel, low-cost directional sensor inspired by insect vision. This work demonstrates how polarized light patterns can be captured with a standard camera to provide reliable heading information, reducing drift in dead-reckoning systems. Wang’s research bridges theoretical algorithm development and practical sensor design, offering scalable solutions for autonomous navigation in complex, unstructured environments.