Papers
6
Total Citations
49
H-Index
4
About
Mengyu Lei is an emerging researcher specializing in robotics, autonomous systems, and intelligent automation for underground coal mine environments. Their work sits at a critical intersection of robotic path planning, computer vision, and mining engineering, addressing some of the most pressing safety and efficiency challenges facing the coal mining industry. Lei's most impactful contributions center on advancing anchor drilling robots and robotic roadheaders. Their development of binocular vision-based positioning for anchor drilling hole location (14 citations) has meaningfully pushed the envelope on automating roof bolt support operations — a process vital for preventing underground collapses. Complementing this, their hybrid visual servo control framework enables high-precision drilling in the notoriously complex conditions of coal mine roadways. On the motion planning side, Lei has pioneered improved RRT-based trajectory algorithms and ant colony optimization methods for energy-efficient cutting paths (16 citations), tackling longstanding inefficiencies in conventional approaches. Their 2025 contributions on inverse kinematics and collision-aware path planning in narrow tunnels demonstrate a broadening research vision extending beyond mining-specific applications toward general robotic systems. With a growing citation profile accumulating nearly 50 citations across recent publications, Lei represents a promising voice in intelligent mining robotics and autonomous underground systems.
Research Focus
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Top Papers
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