Xinming Lu

Papers

Total Citations

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About

Xinming Lu is a leading researcher in intelligent tunneling and mining robotics, with a focus on autonomous navigation and precision control for underground construction machinery. His work addresses the critical challenge of roadheader robotization, where he pioneered multi-sensor fusion techniques that integrate inertial measurement units, total stations, and other sensors to enable real-time posture detection and self-localization in GPS-denied environments. His highly cited 2019 paper, "A Multi-Sensor Based Roadheader Positioning Model and Arbitrary Tunnel Cross Section Automatic Cutting," has garnered 18 citations and lays the foundation for automatic tunneling by allowing roadheaders to autonomously cut arbitrary tunnel cross-sections with high accuracy. This contribution is pivotal for improving safety and efficiency in underground engineering, reducing human error in hazardous environments. Lu’s research bridges mechanical engineering, sensor technology, and control systems, offering practical solutions for the mining and construction industries. His work continues to influence the development of smart, autonomous excavation systems, making him a key figure in advancing robotic tunneling technologies.