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About

Yupeng Chi is a leading researcher in intelligent robotic welding systems, with a focus on advanced computer vision and real-time control for manufacturing automation. His work centers on developing robust, vision-guided solutions for seam tracking and trajectory planning, addressing critical challenges in gas metal arc welding (GMAW). Chi's major contributions include the creation of a pseudo-binocular stereo vision approach for welding trajectory recognition, which enhances accuracy without requiring multiple cameras, and a real-time seam tracking system that integrates extraction and restoration models to maintain precision under dynamic conditions. His most cited paper, "A novel approach for robotic welding trajectory recognition based on pseudo-binocular stereo vision" (2024), has garnered 28 citations, while his other key works, including a versatile system combining laser positioning, trajectory fitting, and real-time tracking (2023), have collectively accumulated over 66 citations. Chi's innovative integration of vision-based methods with adaptive control has significantly improved the reliability and efficiency of automated welding, making his research highly influential in the field of industrial robotics and manufacturing technology.