Point Cloud Based Three-Dimensional Reconstruction and Identification of Initial Welding Position
Point Cloud Based Three-Dimensional Reconstruction and Identification of Initial Welding Position
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DOI：
10.1007/978-981-10-8330-3_4
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Lunzhao Zhang;Yanling Xu;Shaofeng Du;Wenjun Zhao;Zhen Hou;Shanben Chen
中科院分区：
文献类型：
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作者：
Lunzhao Zhang;Yanling Xu;Shaofeng Du;Wenjun Zhao;Zhen Hou;Shanben Chen
焊接初始位置引导是基于视觉的智能化机器人焊接的必要条件。提出了一种基于点云的激光条纹传感器焊接环境识别和初始位置定位方法。经过标定的激光传感器可以实现从图像坐标系到摄像机坐标系以及从机器人工具坐标系到手眼坐标系的高精度转换。该方法首先采用基于线性特征的图像处理算法，以亚像素级的精度提取激光条纹中心位置;然后采用基于队列的插值算法，将下采样的激光点转换为机器人基座坐标系，实现实时扫描。工件的识别是通过从图像中的点云数据分割工件来实现的。在分割之前，构建基于KD树的背景模型，过滤掉背景点;然后采用RANSAC拟合过程剔除离群值，拟合出正确的工件平面模型;并可以沿着焊缝（拟合平面的交集）找到焊接初始位置。在验证实验中，即使存在异常噪声，也能正确识别工件平面和焊接初始位置。
Initial welding position guidance is necessary for vision-based intelligentized robotic welding. In this paper, we proposed a point cloud based approach to recognize working environment and locate welding initial position using laser stripe sensor. Calibrated laser sensor can achieve high accuracy in transforming from image coordinate system to camera coordinate system and to robot tool coordinate system with hand-eye calibration. Linear feature based image processing algorithm is developed to extract the position of laser stripe center in subpixel-level accuracy; then trajectory-queue based interpolation is implemented to convert down-sampled laser points to robot base coordinate system in real-time scanning. Identification of workpiece is implemented by segmenting workpieces from the point cloud data in the image. Before segmentation, KD-Tree based background model is constructed to filter out background points; then RANSAC fitting procedure rejects outliers and fits the correct workpiece plane model; and the welding initial position can be found along the weld seam which is the intersection of fitted planes. In verification experiment, workpiece planes and welding initial position can be correctly recognized despite the presence of abnormal noises.