Papers
4
Total Citations
82
H-Index
3
About
Qiu Tang is a leading researcher in intelligent robotic welding and manufacturing, specializing in the automation of complex pipe and weldment processing. Their work bridges advanced 3D visual perception, offline programming, and multi-objective optimization to solve real-world industrial challenges. Tang’s most cited paper, “A novel offline programming approach of robot welding for multi-pipe intersection structures based on NSGA-Ⅱ and measured 3D point-clouds” (45 citations), introduces a groundbreaking method that uses point-cloud data and evolutionary algorithms to automate welding path planning for intricate pipe intersections—a task traditionally reliant on manual programming. Building on this, their 2024 study on robot welding path autonomous planning (23 citations) further integrates 3D visual perception for real-time adaptability. Tang also contributes to robotic grinding and plasma cutting, with a novel path planning method for free-form weld seams (13 citations) and a model-driven approach for branch pipe cutting. By combining measured 3D data with intelligent algorithms, Tang has significantly advanced the precision and efficiency of robotic manufacturing, offering scalable solutions for industries like shipbuilding and aerospace. Their work is highly cited for its practical impact on automating complex, non-repetitive welding tasks.
Research Focus
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Top Papers
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