基于改进TLD算法的激光视觉传感型焊缝跟踪

A laser vision sensing method for seam tracking based on an improved TLD algorithm

为了解决基于线激光视觉传感的焊缝中心位置定位精度不高的问题,采用了一种基于改进跟踪-学习-检测(TLD)算法的焊缝跟踪方法。由激光视觉传感器实时获取焊缝图像,采用将跟踪器与检测器结合的TLD算法实时跟踪焊缝特征点,同时通过在线学习机制更新分类器参量。在此基础上对激光条纹图像截取感兴趣区域,大幅减少检测器的搜索区域;根据激光条纹光强分布特性,结合纠偏方向选取跟踪器有效特征点,以此提高算法效率,对不锈钢板V型焊缝和搭接焊缝进行跟踪试验。结果表明,跟踪与检测可实现共同定位焊缝中心位置,其融合的焊缝跟踪方法能够准确地提取焊缝特征点,两种焊缝跟踪平均绝对误差分别为0.062mm和0.052mm。此方法为提高焊缝跟踪精度提供了依据。

In order to solve the problem of low positioning accuracy of the weld seam center based on line laser vision sensing,a seam tracking method based on an improved tracking-learning-detection(TLD)algorithm was adopted.The weld images were acquired in real time during the weld seam tracking.The TLD algorithm combining the tracker(tracking)and the detector(detection)was adopted to track weld feature points in real time and the online learning mechanism(learning)was adopted to update the classifier parameters,so as to improve the accuracy of seam tracking.On this basis,the region of interest(ROI)was intercepted from the laser stripe images,which greatly reduced the detector’s search area.The effective feature points of the tracker were selected to improve the efficiency of the algorithm according to the characteristics of the light intensity distribution of the laser stripe in combination with the rectifying direction.The V-shaped weld and the lapped weld of the stainless steel plate were tracked.The results indicate that the location of the seam center can be achieved by tracking and detecting and the fusion weld tracking method can accurately extract weld feature points.The mean absolute tracking errors of both weld seams were 0.062mm and 0.052mm.This method provides the basis for improving the accuracy of weld seam tracking.