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The autonomous detection and guiding of start welding position for arc welding robot

机译:电弧焊机器人起焊位置的自主检测和指导

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Purpose - The recognition and positioning of start welding position (SWP) is the first step and one of the key technologies to realize autonomous robot welding. The purpose of this paper is to describe a method developed to accomplish successful autonomous detection and guiding of SWP. Design/methodology/approach - The images of workpieces are snapped by charge coupled device (CCD) cameras in a relative large range without additional light. The recognized methods of SWP are analyzed according to the given definition. A two-step method named "coarse-to-fine" is proposed to recognize the SWP accurately. The first step is to solve the curve functions of seam and workpieces boundaries by fitting. The intersection point is regarded as initial value of SWP. The second step is to establish a small window that takes the initial value of SWP as centre. Then, the SWP is obtained exactly by corner detection in the window. Both the abundant information of original image and the structured information of recognized image are used according to given rules, which takes full advantage of the image information and improves the recognized precision. Findings - The detected results show that the actual and calculated positions by first step of SWP are identical for regular seam, but different for the irregular curve seam. The exact results can be calculated by the two-step method in the paper for both regular and irregular seams. The typical planar "S-shape" and spatial arc curved seams are selected to carry out autonomous guiding of SWP. Originality/value - The experimental results are given based on the introduction of 3D reconstructed and guided method. The guided precision is less than 1.1 mm, which meets the requirements of practical production. The proposed two-step method recognizes the SWP rapidly and exactly from coarse to fine.
机译:目的-开始焊接位置(SWP)的识别和定位是实现自动机器人焊接的第一步,也是关键技术之一。本文的目的是描述一种为成功完成SWP的自主检测和指导而开发的方法。设计/方法/方法-电荷耦合器件(CCD)相机在相对较大的范围内捕捉工件图像,而无需额外的光线。根据给定的定义分析公认的SWP方法。为了准确识别SWP,提出了一种称为“从粗到细”的两步方法。第一步是通过拟合来解决接缝和工件边界的曲线函数。交点被认为是SWP的初始值。第二步是建立一个小窗口,以SWP的初始值为中心。然后,通过窗口中的拐角检测精确地获得SWP。根据给定的规则使用原始图像的大量信息和识别图像的结构信息,这充分利用了图像信息并提高了识别精度。结果-检测到的结果表明,对于常规缝,SWP第一步的实际位置和计算位置相同,但对于不规则曲线缝,则不同。对于规则和不规则的接缝,可以通过两步法计算出准确的结果。选择典型的平面“ S形”和空间弧形弯曲接缝以进行SWP的自主引导。原创性/价值-在引入3D重构和引导方法的基础上给出了实验结果。导向精度小于1.1mm,满足实际生产的要求。所提出的两步法可以从粗到细快速准确地识别SWP。

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