Xinzhou Qiao
Papers
7
Total Citations
37
H-Index
4
About
Xinzhou Qiao is a leading researcher in cable-driven parallel robotics, with a focused expertise in the design, stability, and control of cable-based robots for challenging industrial environments, particularly in coal mining and sorting applications. His major contributions center on solving the critical stability and tension problems inherent in long-span, high-speed cable robots. Qiao pioneered the use of grey relational analysis for quantitative stability sensitivity assessment, a method he applied to coal-gangue picking robots to establish the relationship between cable tension, position, and structural stability. His work on pick-and-place trajectory planning for cable-based gangue-sorting robots, which addresses model uncertainties and external disturbances through robust adaptive fuzzy tracking control, has garnered 11 citations. Qiao has also advanced the understanding of minimum cable tensions and tension sensitivity for long-span cable-driven camera robots, directly impacting stability analysis. His research extends to dual-arm cutting robots for coal mine laneway excavation, tackling the efficiency bottleneck of traditional methods. With a cumulative citation count exceeding 37, Qiao’s work is instrumental in transitioning cable robots from laboratory concepts to reliable, high-performance systems for real-world mining and industrial automation.
Research Focus
Key Achievements
Top Papers
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- 6On the Equivalent Position Workspace for a Coal Gangue Picking Robot2 citations · 2019
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