Mingle Zhao
Peking University, City University of Macau, University of Macau
Papers
4
Total Citations
15
H-Index
3
About
Mingle Zhao is an emerging researcher specializing in mobile robotics, autonomous navigation, and state estimation, with a particular focus on visual-inertial SLAM systems and localization in challenging environments. His work bridges deep learning and classical robotics to advance the capabilities of low-cost robotic platforms operating in real-world conditions. Zhao's most recognized contribution, "DiT-SLAM" (2022, 7 citations), introduced a real-time dense visual-inertial SLAM framework that leverages implicit depth representations from deep neural networks combined with tightly-coupled graph optimization, enabling more informative and continuous environmental mapping for mobile robots. This work addresses a critical demand in the robotics community for richer, denser scene understanding in real-time. A distinctive thread in Zhao's research is tackling nocturnal localization — a largely unsolved problem. His "Night-Rider" (2024, 3 citations) and "Night-Voyager" (2025, 2 citations) works demonstrate innovative use of standard cameras for nighttime state estimation using streetlight maps and object maps respectively. His additional work on OSM-guided urban mapping with active loop closure further demonstrates his commitment to scalable, practical autonomous systems. Though early in his career, Zhao's focused contributions signal a promising trajectory in robust robotic perception research.
Research Focus
Key Achievements
Top Papers
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