Yongmin Park

Papers

Total Citations

H-Index

About

Yongmin Park’s research focuses on precision manufacturing, robotic vision, and quality control systems, with a particular emphasis on enhancing automation in industrial assembly. His major contributions lie in integrating Kalman filter algorithms with visual robotic control to improve accuracy and reliability in manufacturing processes. In his most cited work, “Enhancing e-quality for manufacture using Kalman Filter calibrated visual robotic control” (2011, 8 citations), Park demonstrates how sensor fusion can correct robotic positioning errors in real time, significantly boosting production quality. His follow-up study, “Sensor-based Remote Quality Control Application in Automotive Components Assembly” (2010, 7 citations), addresses the challenges of geographically dispersed global supply chains, proposing a remote monitoring framework that maintains quality standards across international facilities. Park’s third key paper, “Improvement of vision guided robotic accuracy using Kalman filter” (2011, 5 citations), further refines these techniques, offering a practical solution for reducing calibration drift in automated systems. Though his citation counts are modest, Park’s work is notable for its direct industrial applicability, bridging the gap between theoretical control systems and real-world manufacturing challenges. His research remains relevant for engineers seeking cost-effective, sensor-driven approaches to enhance robotic precision in global production environments.