In the process of spot localization, if the quality of the laser triangular spot image is poor, it will directly affect the accuracy of subsequent spot localization. Therefore, a laser triangular spot localization method based on reinforcement learning is proposed. Collect laser triangular spot images and perform denoising and segmentation on the collected images to remove image noise, obtain spot targets, and improve image quality; Introducing neighborhood calibration light spots to perform cross correlation operations on the processed image, fully utilizing the skewed distribution of light spots and the similarity constraints of their positions, to determine the distribution of correlation coefficients at the target pixel level. Implement cubic non-uniform rational B-spline interpolation subdivision on the obtained correlation coefficient distribution results, establish the center positioning equation of the laser spot based on the subdivision results, optimize the positioning equation using reinforcement learning algorithm, further improve the positioning accuracy, and achieve precise positioning of the laser three corner spot. The experimental results show that using this method for laser triangulation spot positioning has good positioning effect and high accuracy.