Papers
4
Total Citations
101
H-Index
4
About
Guanghui Xue is a leading researcher in intelligent mining technologies, with a focus on transforming China’s coal industry through automation, safety, and efficiency. His work spans computer vision for coal gangue detection, simultaneous localization and mapping (SLAM) for underground environments, and the development of smart mining machinery. Xue’s most cited paper (60 citations) introduces a lightweight YOLO algorithm with a ResNet18 backbone for real-time coal gangue identification, addressing the labor-intensive and hazardous manual sorting process. He further advances underground robotics with an improved LeGO-LOAM algorithm for map construction (22 citations), enabling autonomous navigation in GPS-denied coal mines. His review on intelligent technologies and machinery (11 citations) contextualizes China’s shift toward green, safe, and efficient mining under carbon neutrality goals. Xue also contributes to ground control safety, using Flac3D to determine support bracket resistance in deep roadways (8 citations). His research directly supports the national strategy for intelligent mine construction, reducing human risk while boosting productivity. By integrating deep learning, robotics, and geomechanics, Xue is shaping the next generation of autonomous, safer coal mining systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4