Changqing Yan
Papers
1
Total Citations
18
H-Index
1
About
Changqing Yan is a leading researcher in intelligent mining and tunnel engineering, with a primary focus on autonomous robotic systems for underground construction. His work centers on the critical challenge of enabling roadheaders—massive tunneling machines—to perceive their own posture and location in GPS-denied environments. His most-cited paper, "A Multi-Sensor Based Roadheader Positioning Model and Arbitrary Tunnel Cross Section Automatic Cutting" (2019, 18 citations), proposes a pioneering multi-sensor fusion method that integrates inertial systems for altitude angle measurement, total stations for coordinate tracking, and additional sensors to achieve precise self-localization. This breakthrough directly enables automatic, arbitrary cross-section cutting—a key step toward full roadheader robotization. By solving the fundamental problem of autonomous posture detection, Yan’s research has laid the groundwork for safer, more efficient, and fully automated tunneling operations. His work bridges sensor technology, robotics, and civil engineering, offering practical solutions for the mining and infrastructure industries. With growing citation impact, Changqing Yan continues to shape the future of intelligent excavation systems.
Research Focus
Key Achievements
Top Papers
- 1