A compact algorithm for rectification of stereo pairs
Machine Vision and Applications
Computer Vision
Experiments on automatic seam detection for a MIG welding robot
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Journal of Intelligent and Robotic Systems
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One of the main challenges for robotic welding in low to medium volume manufacturing or repair work is the time taken to programme the robot path for a new job. It is often cheaper and more efficient to weld the parts manually. There are many papers published on the detection of butt welds, however there is no mature method for the identification of fillet welds which are more common. This paper presents a novel method that can autonomously identify fillet weld joints regardless of the base material, surface finish and surface imperfections such as scratches, mill scale and rust. The new method introduces an adaptive line growing algorithm for robust identification of weld joints regardless of the shape of the seam. The proposed method is validated through experiments using an industrial welding robot in a workshop environment. The results show that this method can detect realistic fillet weld joints for industrial arc welding applications.