Zhao Qing

Beijing Jingshida Electromechanical Equipment Research Institute

Papers

Total Citations

H-Index

About

Zhao Qing is a researcher whose work bridges the fields of robotics, intelligent control, and electromechanical systems. Their most recognized contribution, "Neural network technique in camera calibration" (2002, 14 citations), introduced a pioneering approach that leverages artificial neural networks to map 2D image data to 3D spatial information. This method eliminates the need for complex mathematical models or prior knowledge of camera parameters, offering a flexible and robust solution for computer vision tasks. The work remains a foundational reference for researchers exploring learning-based calibration techniques. More recently, Zhao has focused on the practical challenges of robotic actuation, as seen in their 2019 study on frameless motors. This work analyzes the performance of 100W-level frameless motors for robots, optimizing motor design by considering load characteristics to meet the demanding requirements of robotic applications. While the citation count for this paper is modest, it reflects a targeted, application-driven contribution to the growing field of robot hardware. Zhao Qing’s research trajectory demonstrates a commitment to both foundational methods and applied engineering, making their work relevant for students and researchers interested in intelligent systems and robotic design.