Abstract
Aiming at the inconsistency between the coordinate system of target object and the theoretical coordinate system in robot automatic drilling, a visual alignment method by merging 2D/3D data is proposed. The 2D image data and 3D point cloud were acquired by the 3D Imaging System with Structured Light. An improved adaptive threshold and morphological processing algorithm were used to extract the edge features of datum holes. Edge discrimination and Euclidean clustering algorithm was used to calculate the projection points of the holes. Based on binocular stereo vision, the matching relationship between points in left and right images were established through the projection points, and the 3D coordinates of the center of the datum hole were obtained. The coordinate system transformation of the workpiece under the vision system was completed by the theoretical coordinates and the actual coordinates. Experimental results showed that the positioning accuracy of the datum hole of the proposed method was 0.05 mm, which was better than 10% of the traditional method that includes Canny edge detection and epipolar constraint.
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This research is partially supported by the National Natural Science Foundation of China (Grant Nos. 62176149 and 51975344).
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Wu, J., Zhang, X., Tu, D. (2022). Visual Alignment Method by Merging 2D/3D Data in Robot Automatic Drilling. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13458. Springer, Cham. https://doi.org/10.1007/978-3-031-13841-6_24
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DOI: https://doi.org/10.1007/978-3-031-13841-6_24
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