During the production of automotive axle holes, the roundness error at the pipe opening leads to low detection efficiency due to manual measurements, rendering real-time inspection unfeasible.This paper proposes a method for detecting and sorting the roundness of automotive axle holes based on visual inspection.Ensuring accuracy in grasping, it establishes the kinematic model of the robot Aubo_I5.Targeting automotive axle holes for grasping, it employs adaptive threshold segmentation to highlight the section features of the axle hole.The Canny algorithm is then used to extract edge information, and finally, the least squares method is utilized to detect roundness errors for sorting the axle holes based on this error.
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Zhang et al. (2024) studied this question.
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