Surface segmentation and weld extraction on noisy point clouds consisting of multiple quadrics

Quadrics are the most common types of surfaces used in weldments. Extracting multiple welds formed by quadric surfaces from a single 3D point cloud is an essential and challenging step in robotic welding for complex weldments. Relevant studies mostly focus on weld extraction from weldments with a single type of quadric. A weld extraction method for weldments with general quadratic surfaces is required. (1) This paper proposes a quadric fitting method for all kinds of quadrics, efficiently solving the quadric models with linear equations. It can be observed from the test results that the fitting error of the method proposed in this paper grows at a rate of about 1/5 of that of the SVD method in the literature as the point cloud noise grows; and the method proposed in this paper improves the operating efficiency by about 40 %. (2) For noisy point clouds with multiple intersecting quadrics, a quadric segmentation method based on region growing is proposed. The proposed segmentation method reduces 30 % ∼ 50 % of segmentation errors during the tests compared to the ICP registration approach in the literature. (3) A region growing method based on ETVPS (End Tangent Vector Projection Sorting) for weld extraction with the unorganized raw intersection points from the segmented quadrics is proposed. All the mentioned methods are verified with solid experiments with physical weldments. The proposed weld extraction method proves to be robust to noisy and defective point clouds.