• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.209-216
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• 2023

This paper aims to develop a model to estimate the paint thickness in a shipyard spray painting according to changes of spraying distance and speed. We acquired the experimental datasets of five different conditions with respect to the spraying distance and speed using a painting robot. In addition, we applied a preprocessing step to handle noises which might be caused by various reasons such as a nozzle damage. Our method is to transform a thickness function of a specified spraying distance and speed into another function of an unknown spraying and speed. We observed that the proposed method shows more stable and more accurate predictions compared with an artificial neural network-based approach.