Modeling of Coating Growth Rate for Digital Camouflage Robotic Spraying Based on Elliptic Double $\beta$ Models

With the advancement of robot technology and the improvement of spraying process requirements, camouflage pattern painting of the equipment is gradually evolved from traditional manual spraying towards automatic robot spraying. In this paper, addressing the challenge of modeling coating growth rate in digital camouflage robot spraying, a mathematical model of coating growth rate based on elliptic double
$\beta$
distribution is proposed and its simple solution method are proposed, according to the unique spraying distribution characteristics of the spray gun. Through meticulously designed spraying experiments, comprehensive data sets pertaining to coating thickness and spraying width under varying conditions of spraying speed and distance are collected, and the least squares method is used to fit the model and solve the model parameters by measured data, and analyzing discrepancies between model predictions and actual measurements. The experimental results show that the coating growth rate model for digital camouflage robot spraying has good fitting accuracy, and can provide spraying process parameters such as gun speed and spraying distance for automatic robot spraying path planning.