Clamping error during automatic welding of axle housing will lead to weld deviation. To that end, a method for axle housing weld seam localization based on monocular vision is proposed in this paper. Firstly, a method of extracting weld seam centerline based on template matching and iterated least squares fitting is proposed according to the grayscale of axle housing image. Then, the end points of weld seam are searched through the gray feature of axle housing on the weld seam centerline. Finally, the mapping relationship between image coordinate system and robot coordinate system is established by calibration. According to the deviation between actual position and standard position of weld under image coordinate system, the actual three-dimensional coordinate of weld in robot coordinate system is found by particle swarm optimization algorithm. The experimental results show that the maximum error of the weld seam endpoints obtained by this method in the x, y axis is less than 0.5mm, and the maximum error in the z axis is less than 0.9mm, which meets the requirements of axle housing automatic welding. This method only uses one monocular camera, and has a low cost while ensuring the positioning accuracy through calibration and optimization algorithms.
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