焊接
排队
曲线拟合
跟踪(教育)
点(几何)
计算机科学
过程(计算)
起点
沟槽(工程)
机器人焊接
弹道
机器人
曲率
算法
计算机视觉
人工智能
工程类
机械工程
几何学
数学
心理学
教育学
物理
天文
机器学习
程序设计语言
操作系统
作者
Yunkai Ma,Junfeng Fan,Sai Deng,Yu Luo,Xihong Ma,Fengshui Jing,Min Tan
标识
DOI:10.1109/tim.2021.3072103
摘要
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.
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