Papers
3
Total Citations
41
H-Index
3
About
Qingyi Shi is a robotics researcher specializing in the trajectory optimization and control of wall-building robots operating in uncertain viscoelastic contact environments. Their major contributions lie in developing multi-objective optimization frameworks that balance competing demands: reducing energy consumption, minimizing contact forces, improving masonry quality, and enhancing work efficiency. Shi’s most cited work, “Trajectory optimization of wall-building robots using response surface and non-dominated sorting genetic algorithm III” (2023, 22 citations), introduces a novel approach combining response surface methodology with NSGA-III to achieve superior trajectory planning. This is complemented by their 2023 study (14 citations) employing RBF-NSGA-II for segmented multi-objective trajectory optimization, which directly addresses the challenges of uncertain viscoelastic interactions. Shi’s research has practical implications for construction automation, enabling robots to perform precise, energy-efficient bricklaying in complex environments. Their work on trajectory tracking control (2024, 5 citations) further advances real-time adaptability. With a focused portfolio of high-impact papers, Shi is establishing themselves as a key contributor to the intersection of robotics, optimization, and construction technology.
Research Focus
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Top Papers
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