Xiaoqi Nong

Wuhan University of Science and Technology, University of Surrey

Papers

Total Citations

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About

Xiaoqi Nong is a robotics researcher whose work centers on advancing mobile robot positioning and navigation, particularly in GPS-denied indoor environments. His research integrates inertial navigation systems (INS), binocular vision, and ultrasonic sensors to overcome the limitations of individual positioning methods. Nong’s most cited paper (2017, 13 citations) introduces an asynchronous fusion of binocular vision and INS, using a fuzzy map to mitigate the drift and environmental constraints of each system—a practical solution for real-world robot autonomy. His follow-up work (2017, 5 citations) further refines indoor navigation by pairing low-cost INS with ultrasonic sensors to correct magnetic interference and cumulative error. More recently, Nong has pushed into event-based sensing with ASL-SLAM (2022, 2 citations), the first line-based SLAM system operating solely on event sensors. This asynchronous formulation maximizes the high-speed, low-latency advantages of event cameras, marking a significant step toward more efficient, robust navigation for industrial automation. With a growing citation footprint and a clear trajectory from sensor fusion to cutting-edge event-based SLAM, Nong’s contributions are shaping the future of autonomous mobile robotics.