Ruoqi Wang
Papers
3
Total Citations
113
H-Index
3
About
Ruoqi Wang is a leading researcher in robotic machining and manufacturing dynamics, with a focus on improving precision and stability in complex machining processes. Their work centers on predicting and controlling chatter—a detrimental vibration that compromises surface quality and tool life—in robotic milling operations. Wang’s most influential paper, “Prediction of pose-dependent modal properties and stability limits in robotic ball-end milling” (2021, 56 citations), established a foundational framework for understanding how a robot’s configuration affects its dynamic behavior and machining stability. Building on this, they advanced dual-robot collaborative machining systems for thin-walled parts, a critical challenge in aerospace and automotive industries. Their 2024 paper on chatter prediction for parallel mirror milling (34 citations) and their work on a stiffness matching-based deformation error control strategy (23 citations) demonstrate innovative approaches to synchronizing multiple robots to minimize deflection and vibration. With over 100 citations across their top papers, Wang’s contributions are shaping the next generation of flexible, high-precision robotic manufacturing, offering practical solutions for industries requiring lightweight, complex components.
Research Focus
Key Achievements
Top Papers
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