Mingqiang Lin

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About

Mingqiang Lin is a researcher specializing in sensor calibration, robotic positioning, and 3D reconstruction, with a focus on enhancing the accuracy and practicality of measurement systems for industrial and medical robotics. His most influential work, an improved calibration method for rotating 2D LIDAR systems (2018, 48 citations), addresses a critical challenge in obtaining reliable 3D environmental scans by refining the alignment of a 2D LIDAR mounted on a rotating unit—a technique widely used in autonomous navigation and mapping. Lin also investigates industrial robot precision, analyzing dynamic path accuracy in six-axis robots using optical trackers (2017), a study that highlights the gap between theoretical calibration and real-world application, where absolute positioning remains difficult for end-users. In medical robotics, he proposed a novel reconstruction model for multi-camera positioning systems based on neural networks (2018), aiming to improve 3D reconstruction accuracy in surgical settings. Together, these contributions underscore Lin’s commitment to bridging the gap between sensor theory and practical deployment, offering scalable solutions for high-stakes environments like manufacturing and surgery. His work continues to inform advancements in robotic perception and calibration.