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Target recognition and positioning method for steel structure spraying robot based on binocular vision

Aiming at the problem of spraying target identification and positioning of steel structure fireproof coating spraying robot, the stereo imaging model of binocular camera is established, and the collected binocular images are preprocessed by distortion correction and epipolar rectification. The application of multi-grid method in stereo matching and depth image calculation were studied, and the effect of multi-layer perceptron neural networks classifier (MLP) on segmentation of steel structure region in color image was researched. The experimental results in real scenes show that the error between the binocular vision measurement results and the actual distance is less than 2.5%. MLP classifier can effectively separate the target region from the color image, and further crop the depth image in this region to obtain the depth image containing only the target information.