Papers
4
Total Citations
37
H-Index
3
About
Zheng Dong is an emerging researcher specializing in intelligent robotics, autonomous systems, and automation technologies for underground coal mining environments. His work sits at a critical intersection of computer vision, path planning, and robotic control, addressing some of the most pressing safety and efficiency challenges facing the mining industry. Dong's most influential contribution to date applies ant colony optimization to energy-efficient cutting trajectory planning for axial robotic roadheaders, garnering 16 citations since its 2024 publication — a remarkable uptake for such a recent work. His research on binocular vision-based anchor drilling hole localization (14 citations) demonstrates a practical commitment to enhancing automation in roof bolt support operations, directly reducing accident risks in hazardous roadway environments. Complementing this, his work on hybrid visual servo control enables high-precision drilling by anchor-drilling robots, pushing the boundaries of autonomous underground operations. More recently, Dong has tackled the complex challenge of safe path planning for robotic roadheaders navigating narrow tunnels, introducing collision prediction frameworks suited to constrained underground geometries. Collectively, his research portfolio signals a focused mission: transforming dangerous manual mining operations into safe, intelligent, and automated systems — a contribution with significant real-world implications for worker safety and operational efficiency.
Research Focus
Key Achievements
Top Papers
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