Papers
1
Total Citations
5
H-Index
1
About
Yaming Cao is a researcher specializing in robotic laser welding and real-time optical sensing systems. His work focuses on advancing automated manufacturing through the integration of computer vision and robotics, particularly for high-precision industrial applications. Cao’s most cited paper, “Real-Time Implementation of a Joint Tracking System in Robotic Laser Welding Based on Optical Camera” (2018), presents a novel approach to seam tracking that enables robots to adaptively correct welding paths in real time using optical camera feedback. This contribution addresses critical challenges in laser welding, such as joint misalignment and thermal distortion, improving both accuracy and efficiency in automated production lines. With 5 citations, this work has informed subsequent studies in adaptive welding control and sensor-guided robotics. Cao’s research bridges the gap between theoretical vision algorithms and practical industrial deployment, demonstrating how low-cost optical systems can replace expensive laser trackers. His achievements highlight the potential of real-time feedback systems to enhance quality control in manufacturing, making him a notable contributor to the field of intelligent robotic welding.
Research Focus
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Top Papers
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