Hongyue Chen

Papers

Total Citations

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About

Hongyue Chen is a specialist in underground mining robotics and automation, with research focused on the design, control, and intelligent operation of robotic systems for coal mine environments. Over more than a decade of work, Chen has made notable contributions to some of the most technically demanding challenges in mining automation, including the development of control methods for coal mine roadway support robots (CMRSRs), virtual simulation of tunnel profiling cutting, and sensor-based detection systems for roadheader equipment. Chen's most recognized work, published in 2023 and accumulating 7 citations, introduces an innovative expected position-attitude adjustment control method for CMRSRs, leveraging real-time detection systems to enhance operational flexibility and safety underground. Earlier contributions, including a 2009 study on virtual simulation of memory-profiling cutting for tunnel robots and a 2011 investigation into triaxial digital acceleration sensors for boom angle detection, demonstrate a consistent long-term commitment to advancing roadheader automation and precision control. Collectively, Chen's research addresses critical engineering barriers in mine robotics — from structural modeling to real-time sensing — helping to push the field toward safer and more autonomous underground operations. With a growing citation record, Chen's work offers valuable technical insights for researchers and engineers working at the intersection of robotics, mining engineering, and industrial automation.