Start point guiding and seam tracking are important parts of the robot’s intelligent welding process. However, some start point guiding methods have a large amount of calculation and low accuracy. In addition, due to the large curvature of the curved weld, the problem of visual advance in seam tracking should be solved. Therefore, an efficient and accurate start point guiding and seam tracking method for curve weld is proposed in this article. First, according to the characteristics of structural light of different welds, more efficient and accurate start point detection algorithms are proposed for curve v-groove welds and curve lap welds. The extraction of key characteristic points and the judgment of the relationship between them could achieve efficient weld start point detection, and the reasonable robot speed planning during the start point searching process could improve the accuracy of the start point guiding. Besides, a sliding data queue method with cubic B-spline fitting is proposed to overcome the visual advance problem and achieve accurate seam tracking of curve welds. The sliding data queue method can plan the data queue automatically, and improve the computational efficiency by reducing the amount of data to be processed. Cubic B-spline fitting can reduce the measurement error and eliminate the data fluctuation, so as to obtain a smooth welding trajectory. The experimental results show that the proposed method could achieve efficient and accurate start point guiding and seam tracking of curve v-groove weld and lap weld.

中文翻译：

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基于结构光的高效准确曲线焊缝起点引导及焊缝跟踪方法


起始点引导和焊缝跟踪是机器人智能焊接过程的重要组成部分。但一些起点引导方法计算量大、精度低。另外，由于弯曲焊缝的曲率较大，需要解决焊缝跟踪的视觉超前问题。因此，本文提出了一种高效、准确的曲线焊缝起点引导和焊缝跟踪方法。首先，根据不同焊缝的结构光特点，针对曲线V型坡口焊缝和曲线搭接焊缝提出了更加高效、准确的起点检测算法。关键特征点的提取以及它们之间关系的判断可以实现高效的焊接起点检测，而起点搜索过程中合理的机器人速度规划可以提高起点引导的准确性。此外，提出了一种三次B样条拟合的滑动数据队列方法来克服视觉超前问题，实现曲线焊缝的精确焊缝跟踪。滑动数据队列方法可以自动规划数据队列，通过减少需要处理的数据量来提高计算效率。三次B样条拟合可以减小测量误差，消除数据波动，从而获得平滑的焊接轨迹。实验结果表明，该方法能够实现曲线V型坡口焊缝和搭接焊缝高效、准确的起点引导和焊缝跟踪。