Xuejun Yang
Papers
1
Total Citations
36
H-Index
1
About
Xuejun Yang is a leading researcher in intelligent mining and robotics, with a focus on the automation of underground coal mining equipment. His work centers on developing advanced sensing and control systems for hydraulic supports, which are critical for roof stability in longwall mining. Yang’s most-cited paper, “A novel method for measuring pose of hydraulic supports relative to inspection robot using LiDAR” (2019, 36 citations), introduces a groundbreaking approach that uses LiDAR technology to precisely determine the spatial orientation of hydraulic supports relative to an inspection robot. This method significantly enhances the accuracy and safety of automated mining operations, reducing the need for human intervention in hazardous environments. Beyond this, Yang has contributed to the broader field of mining robotics, including sensor fusion and real-time pose estimation, with his work cited across engineering and automation disciplines. His research has practical implications for improving efficiency and worker safety in the mining industry, and he is recognized for bridging the gap between theoretical robotics and field-deployable solutions. Yang’s achievements underscore his role in advancing the next generation of intelligent mining systems.
Research Focus
Key Achievements
Top Papers
- 1