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About

Yabin Ding is a robotics and automation researcher whose work spans machine vision, sensor calibration, robot kinematics, and large-scale manufacturing systems. With a career trajectory that moves from industrial automation fundamentals to sophisticated multi-sensor integration, Ding has established himself as a versatile contributor to intelligent robotic systems. His most-cited work (31 citations) introduced a machine vision-guided high-speed sorting system using Delta robots, demonstrating practical solutions for dynamic pick-and-place tasks on production lines. This early contribution laid the groundwork for his sustained interest in vision-based robot control. Ding has since made significant advances in hand-eye calibration — a critical challenge in precision robotics — developing methods that account for robot geometric parameter inaccuracies and three-dimensional sensing, earning over 39 combined citations across multiple studies. His research portfolio also encompasses LiDAR-camera fusion for environmental perception, monocular pose estimation for space applications, and trajectory planning for Delta robots balancing motion smoothness with structural stress. Notably, Ding has contributed to mobile robotic systems for large-scale machining operations, reflecting a commitment to bridging theoretical robotics with demanding real-world manufacturing challenges. Across his body of work, Ding's cumulative citation impact underscores his relevance to researchers working at the intersection of computer vision and advanced robotics.