An Underwater Structured Light Vision Calibration Method Considering Unknown Refractive Index Based on Aquila Optimizer

Underwater structured light vision systems have attracted the attention of researchers because of their high measurement accuracy and robustness. At present, most underwater structured light vision measurement systems consider the refractive index as a known parameter. However, the refractive index of water will change because of environmental changes such as salinity and temperature. Inaccurate refractive index will have serious influence on the measurement accuracy of the underwater structured light vision system. Therefore, an underwater structured light vision calibration method considering unknown refractive index is proposed. To avoid complex calibration process and complex solution process of a nonlinear underwater structured light vision model, a novel checkerboard usage calibration method based on Aquila Optimizer (AO) is proposed. The calibration solution process is regarded as a nonlinear optimization problem, and the optimization objective is established with the distance between the feature points intersected by the checkerboard and the laser. Finally, calibration and measurement experiments are carried out to verify the effectiveness and superiority of the proposed method.