Papers
16
Total Citations
455
H-Index
9
About
Menggang Li is a leading researcher at the intersection of robotics, autonomous navigation, and underground mining technology, with a career dedicated to solving the complex localization and mapping challenges inherent to hazardous subterranean environments. His most influential contribution — a UWB-based localization system augmented with inertial sensors for underground coal mines (2020, 148 citations) — established a new benchmark for positioning accuracy in GPS-denied environments. Complementing this, his widely cited review of Visual-Inertial SLAM (2018, 122 citations) has become an essential reference for researchers navigating the filtering- and optimization-based approaches to autonomous mapping, demonstrating his capacity to synthesize and advance the broader robotics field. Li has been particularly instrumental in developing coal mine rescue robots, contributing both efficient 3D laser-based SLAM systems and explosion-proof locomotion hardware designed to function safely amid post-disaster conditions. His more recent work extends these foundations into practical infrastructure monitoring, including robotic inspection of monorail crane tracks and mine wind shafts, reflecting a deliberate evolution toward real-world deployment. With over 420 cumulative citations, Li's research portfolio uniquely bridges theoretical SLAM methodology with life-critical engineering applications, making him an indispensable voice in intelligent mining robotics.
Research Focus
Key Achievements
Top Papers
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- 3Efficient Laser-Based 3D SLAM for Coal Mine Rescue Robots60 citations · 2018
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- 10Efficient Laser-Based 3D SLAM in Real Time for Coal Mine Rescue Robots8 citations · 2018