Research on Welding Path Planning of Medium-thick Plate Based on the Data Driven of Point Cloud

LI Bingcong; XIA Weisheng; XU Xiaoqun; LV Weiwen

doi:10.7512/j.issn.1001-2303.2023.09.10

Human-machine Cooperation & Intelligent Welding | Views : 0 下载量: 15 CSCD: 0

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Research on Welding Path Planning of Medium-thick Plate Based on the Data Driven of Point Cloud
Vol. 53, Issue 9, Pages: 78-83(2023)
DOI： 10.7512/j.issn.1001-2303.2023.09.10

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李秉聪，夏卫生，许晓群，等.基于点云数据驱动的中厚板机器人焊接路径规划［J］.电焊机，2023，53（9）：78-83.

LI Bingcong, XIA Weisheng, XU Xiaoqun, et al.Research on Welding Path Planning of Medium-thick Plate Based on the Data Driven of Point Cloud[J].Electric Welding Machine, 2023, 53(9): 78-83.
李秉聪，夏卫生，许晓群，等.基于点云数据驱动的中厚板机器人焊接路径规划［J］.电焊机，2023，53（9）：78-83. DOI： 10.7512/j.issn.1001-2303.2023.09.10.

LI Bingcong, XIA Weisheng, XU Xiaoqun, et al.Research on Welding Path Planning of Medium-thick Plate Based on the Data Driven of Point Cloud[J].Electric Welding Machine, 2023, 53(9): 78-83. DOI： 10.7512/j.issn.1001-2303.2023.09.10.

摘要

为实现中厚板多层多道自动化焊接的需求，提出一种基于点云数据驱动的机器人焊接路径自适应规划算法。以V形焊缝为例，首先通过线结构光扫描焊缝表面采集点云数据，对点云数据进行滤波预处理，在精简数据量的同时也去除噪声点，据此采用点云分割和边缘提取算法成功提取焊缝特征点。最终通过焊接实验验证算法的准确性和可行性，结果表明，提出的算法处理得到的焊缝特征点坐标与人工示教得到的实际坐标偏差小于0.17 mm，能够满足实际应用需求。

Abstract

In order to address the automation requirements of multi-layer and multi-pass welding for medium-thick plates, this paper proposes a robot welding path adaptive planning algorithm based on point cloud data. Taking V-groove welds as an example, the weld surface is scanned using a line structured light system to collect point cloud data. Then the point cloud data is preprocessed through the filtering method to reduce the data size and remove noise points, and the resultant welding feature points are successfully extracted by the point cloud segmentation and edge extraction algorithms. Finally, welding experiments are carried out to verify the accuracy and feasibility of the proposed algorithm. The results show that the average deviation between the coordinates of weld feature points obtained by the proposed algorithm and the actual coordinates obtained by manual teaching is less than 0.17 mm, which meets the practical application requirements.

关键词

机器人焊接点云数据驱动多层多道焊接路径规划线结构光

Keywords

robot weldingpoint cloud data-drivenmulti-layer multi-pass weldingpath planningline structured light

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