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A geometry based feature detection method of V-groove weld seams for thick plate welding robots

机译:基于几何的厚板焊接机器人V型槽焊缝特征检测方法

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The precise positions of feature points in the image space are crucial for tracking systems of welding robots. And hence the quality of feature detection directly affects the accuracy of the motion of the welding robots. Moreover, a low computational cost is also needed in a real-time tracking system. This paper presents a method which effectively detects the features of the V-groove weld seam based on their geometries. A camera and a cross-line structured light are constructed to be used as the visual sensing system. Firstly, the skeletonization has applied to the image. Subsequently, Hough transform is used to find the main line of the light stripe. Secondly, The farthest point algorithm is used to estimate the bottom feature point of the weld seam. Finally, the left and right feature points are estimated by the least squares line fitting method. The experimental results show that the features can be precisely recognised by the proposed method. In addition, the computational cost of the proposed method is not expensive, and thus it satisfies the requirement of a real-time system.
机译:特征点在图像空间中的精确位置对于焊接机器人的跟踪系统至关重要。因此,特征检测的质量直接影响焊接机器人运动的准确性。此外,在实时跟踪系统中还需要低的计算成本。本文提出了一种基于几何形状有效检测V型槽焊缝特征的方法。照相机和交叉线结构的光被构造为用作视觉感测系统。首先,骨架化已应用于图像。随后,使用霍夫变换找到光条的主线。其次,使用最远点算法估计焊缝的底部特征点。最后,通过最小二乘线拟合法估计左右特征点。实验结果表明,该方法可以准确识别特征。另外,所提出方法的计算成本并不昂贵,因此可以满足实时系统的要求。

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