基于最佳射击位置的点云焊缝检测

T. Takubo, E. Miyake, A. Ueno, Masaki Kubo
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引用次数: 0

摘要

提出了一种利用点云数据进行焊缝检测的方法,结合接触式传感器实现焊接作业的自动化。所提出的系统的目标是角焊缝,其中垂直连接的两个金属板之间的连接线被焊接。该方法以单一视点为粗测点,检测两块平板的位置和方向后,从各平面的最佳射击位置对平板进行详细测量,以检测出精确的焊缝。当从一个角度测量平板时,深度相机获得的三维点云存在测量误差。例如,由于光反射,测量平面的点云具有波浪形状或空洞。然而,通过垂直拍摄平面,点云的误差更小。利用这些特点,提出了一种确定焊缝的两步测量算法。焊缝检测结果表明,与粗糙和精密测量相比,焊缝检测精度提高了5mm。平均测量误差小于2.5 mm,可以缩小搜索对象接触式传感器的范围,实现焊接自动化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Welding Line Detection Using Point Clouds from Optimal Shooting Position
A method for welding line detection using point cloud data is proposed to automate welding operations combined with a contact sensor. The proposed system targets a fillet weld, in which the joint line between two metal plates attached vertically is welded. In the proposed method, after detecting the position and orientation of two flat plates regarding a single viewpoint as a rough measurement, the flat plates are measured from the optimal shooting position in each plane in detail to detect a precise weld line. When measuring a flat plate from an angle, the 3D point cloud obtained by a depth camera contains measurement errors. For example, a point cloud measuring a plane has a wavy shape or void owing to light reflection. However, by shooting the plane vertically, the point cloud has fewer errors. Using these characteristics, a two-step measurement algorithm for determining weld lines was proposed. The weld line detection results show an improvement of 5 mm compared with the rough and precise measurements. Furthermore, the average measurement error was less than 2.5 mm, and it is possible to narrow the range of the search object contact sensor for welding automation.
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