Papers
1
Total Citations
4
H-Index
1
About
Yao Jian is a leading researcher in intelligent mining robotics, with a primary focus on improving the stability and efficiency of automated excavation systems in challenging geological environments. His most cited work, "Full coverage cutting path planning of robotized roadheader to improve cutting stability of the coal lane cross-section containing gangue" (2021), addresses a critical challenge in underground mining: the presence of gangue—hard, abrasive rock mixed with coal—which causes severe pick wear, excessive vibration, and reduced equipment lifespan. By developing a novel path planning algorithm for full-coverage cutting, Yao’s research directly enhances the operational stability and durability of robotized roadheaders, offering a practical solution to a long-standing industry problem. With 4 citations, this work has already influenced subsequent studies in mining robotics and automation. Yao’s contributions are notable for bridging theoretical path optimization with real-world mining constraints, positioning him as a key innovator in the field of intelligent excavation. His research holds significant promise for safer, more efficient, and cost-effective coal mining operations.
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Top Papers
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