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About

Ziqiang Yin is a pioneering researcher in intelligent robotic welding and remanufacturing systems, with a focus on laser vision sensing and automation. His work centers on developing real-time welding seam detection and tracking technologies, where his most cited paper (2020, 10 citations) introduces a laser vision-based method that enables robots to autonomously identify and follow weld paths—a critical advancement for industrial automation. Yin also made foundational contributions to 3D vision for remanufacturing, designing a structured light sensor (2012, 3 citations) that rapidly models worn parts for robotic repair, addressing the high uncertainty in production processes. His research extends to remote welding systems using power line communication (2019, 3 citations), supporting national infrastructure projects by enabling precise robot control from a distance. Additionally, he developed automated path generation for robot MAG surfacing (2012, 2 citations), streamlining complex remanufacturing workflows. Through these innovations, Yin has advanced the integration of computer vision and robotics in manufacturing, enhancing both productivity and sustainability. His work remains influential for engineers and researchers seeking to automate welding processes and extend component lifecycles.