Papers
25
Total Citations
405
H-Index
9
About
Chaoquan Tang is a robotics researcher whose work sits at the intersection of autonomous systems, localization, and intelligent robotics, with a particular focus on the uniquely challenging environments found in underground coal mines. His research has made significant contributions to making mining operations safer and more efficient by developing robotic solutions that reduce human exposure to hazardous conditions. Tang's most influential work, "UWB-Based Localization System Aided With Inertial Sensor for Underground Coal Mine Applications" (2020, 148 citations), established a foundational framework for positioning coal mine robots in GPS-denied, signal-degraded environments. Complementing this, his 2018 paper on laser-based 3D SLAM for rescue robots (60 citations) advanced autonomous navigation capabilities critical for post-disaster exploration. His development of coal mine rescue robots, documented across multiple publications, addresses the life-threatening realities of explosion aftermath scenarios. Beyond rescue applications, Tang has pioneered inspection robotics for hoisting systems, monorail crane tracks, and ventilation shafts, systematically replacing dangerous manual inspection routines with automated solutions. His earlier work on snake robots and biomimetic locomotion reveals a broad theoretical foundation underpinning his applied research. Collectively, Tang's portfolio demonstrates a sustained commitment to transforming underground mining through intelligent, autonomous robotic systems that protect human lives.
Research Focus
Key Achievements
Top Papers
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- 2Efficient Laser-Based 3D SLAM for Coal Mine Rescue Robots60 citations · 2018
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- 8Modeling and Mechanical Analysis of Snake Robots on Cylinders10 citations · 2019
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