Ou Jing

Papers

Total Citations

181

H-Index

About

Dr. Ou Jing is a leading figure in industrial robotics, whose work has fundamentally advanced the precision and reliability of automated manufacturing systems. His primary research focuses on kinematic calibration, optimization algorithms, and robotic error compensation. Dr. Jing is best known for pioneering a hybrid calibration method that synergizes the Levenberg-Marquardt algorithm with Differential Evolution, a breakthrough detailed in his highly influential 2021 paper. This work, which has garnered 181 citations, provides a robust solution for identifying and correcting kinematic parameter errors in industrial robots, dramatically improving their absolute positioning accuracy without costly hardware modifications. The impact of his research is profound, offering a practical, data-driven pathway to enhance the performance of robots used in aerospace, automotive, and precision assembly. By bridging theoretical optimization with real-world robotic applications, Dr. Jing has established himself as a key innovator in the field, with his methodologies now serving as a benchmark for subsequent calibration studies.