Yongxue Chen
Papers
4
Total Citations
69
H-Index
4
About
Yongxue Chen is a leading researcher in robotic manufacturing, specializing in the optimization of machining processes for complex surfaces. His core contributions lie at the intersection of robotics, toolpath planning, and kinematic optimization, where he has developed novel methods to enhance the precision, efficiency, and stiffness of robotic milling operations. Chen’s most influential work, "Posture Optimization in Robotic Flat-End Milling Based on Sequential Quadratic Programming" (2023, 24 citations), introduces a rigorous framework for solving tool orientation and robot redundancy, directly improving surface quality in high-flexibility machining. He further advanced the field with "Toolpath Generation for Robotic Flank Milling via Smoothness and Stiffness Optimization" (17 citations), addressing critical trade-offs in path continuity and structural rigidity. His recent co-optimization approach (2025, 16 citations) concurrently optimizes tool orientations, kinematic redundancy, and waypoint timing, offering a scalable solution for large-scale robot-assisted manufacturing. Chen’s work is notable for its practical impact on industrial automation, bridging theoretical optimization with real-world machining constraints. With a growing citation record and a focus on collision-free, jerk-constrained trajectory generation (12 citations), he continues to shape the future of intelligent robotic systems for high-precision manufacturing.
Research Focus
Key Achievements
Top Papers
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