Yingxin Ye
Papers
3
Total Citations
84
H-Index
2
About
Dr. Yingxin Ye is a leading researcher in intelligent robotic manufacturing, with a focus on robotic welding, machining, and dynamic modeling. Her work addresses critical challenges in industrial robotics, including process planning, posture optimization, and real-time performance prediction. Dr. Ye’s most cited paper, “A welding task data model for intelligent process planning of robotic welding” (2020, 72 citations), provides a foundational framework for automating welding operations, significantly enhancing efficiency and precision in manufacturing. She further advanced robotic machining with her study on “Redundant Posture Optimization for 6R Robotic Milling” (2022, 10 citations), where she developed a piecewise-global-optimization strategy to improve stiffness, avoid singularities, and respect joint limits—key issues for expanding the use of industrial robots in high-precision tasks. Most recently, her 2025 work on “Hybrid-Driven Dynamic Position Prediction of Robot End-Effector” (2 citations) introduces a novel approach combining parametric dynamic models with machine learning to predict robot behavior, enabling production optimization before actual operation. Dr. Ye’s research is pivotal for advancing smart manufacturing, and her contributions continue to shape the future of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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