Abstract
To make robotic welding more flexible, vision systems are used to detect the weld seam and plan a path for the robot to follow. In this paper an image processing technique is introduced that can automatically detect the weld seam in a “butt-weld” configuration. This method is an improvement on the existing K-Cosine algorithm. The 3D location of weld points is determined using a robot Hand-in-Eye stereo vision system. This paper will also introduce a practical method for robot and Hand/Eye calibration. The validity of these methods will be verified through experiments using a MIG welding robot.
This work is supported by the Australian Research Council under project ID LP0991108 and the Lincoln Electric Company (Australia).
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Dinham, M., Fang, G., Zou, J.J. (2011). Experiments on Automatic Seam Detection for a MIG Welding Robot. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_49
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DOI: https://doi.org/10.1007/978-3-642-23887-1_49
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