Abstract: Aiming at the problem that the traditional automobile insurance tablets can not meet the batch insertion of the factory by manual plugging, an automatic interpolation algorithm based on deep learning is proposed. The method uses the CCD industrial camera combined with the telecentric lens to collect the image information of the insurance film. The acquired image is preprocessed by Gauss-median filtering. Using the KNN algorithm to match the position of the fuse insert slot of the fuse box, use the Faster R-CNN network to identify the location of the fuse, use algorithm to accurately identify the 9 colors of the fuse, and finally the SCARA four-axis robot automatically completes the docking. operating. After the experimental design of this paper, the accuracy of the identification of the common 9 colors of the insurance film can reach 99.8%, and the average period of the insertion of the insurance piece is 1s and 1.5s, the SCARA robot simultaneously inserts insurance for 6 car insurance boxes. The accuracy of the film is over 96.87%.