Knowledge Commons of Institute of Automation,CAS
An Efficient and Robust Complex Weld Seam Feature Point Extraction Method for Seam Tracking and Posture Adjustment | |
Yunkai Ma1; Junfeng Fan1; Huizhen Yang2; Hongliang Wang3; Shiyu Xing1; Fengshui Jing1; Min Tan1 | |
发表期刊 | IEEE Transactions on Industrial Informatics |
ISSN | 1941-0050 |
2023 | |
卷号 | 19期号:11页码:10704 - 10715 |
通讯作者 | Fan, Junfeng(junfeng.fan@ia.ac.cn) |
文章类型 | Research paper |
摘要 | To realize high-quality robotic welding, an efficient and robust complex weld seam feature point extraction method based on a deep neural network (ShuffleYOLO) is proposed for seam tracking and posture adjustment. The Shuffle-YOLO model can accurately extract the feature points of butt joints, lap joints, and irregular joints, and the model can also work well despite strong arc radiation and spatters. Based on the nearest neighbor algorithm and cubic B-spline curve-fitting algorithm, the position and posture models of the complex spatially curved weld seams are established. The robot welding posture adjustment and high-precision seam tracking of complex spatially curved weld seams are realized. Experiments show that the method proposed in this article can extract weld seam feature points quickly and robustly, which enables welding robots to accurately track the weld seams and adjust the welding torch postures simultaneously. |
关键词 | Complex spatially curved weld seam laser visual sensor posture adjustment robot welding seam tracking weld seam feature point (WSFP) extraction |
DOI | 10.1109/TII.2023.3241595 |
关键词[WOS] | CONVOLUTION OPERATOR ; SYSTEM ; POSITION ; CAMERA |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[62173327] ; National Natural Science Foundation of China[62003341] ; Youth Innovation Promotion Association, Chinese Academy of Sciences[2022130] |
项目资助者 | National Natural Science Foundation of China ; Youth Innovation Promotion Association, Chinese Academy of Sciences |
WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
WOS类目 | Automation & Control Systems ; Computer Science, Interdisciplinary Applications ; Engineering, Industrial |
WOS记录号 | WOS:001181996300009 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 机器人感知与决策 |
国重实验室规划方向分类 | 实体人工智能系统感认知 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/52453 |
专题 | 多模态人工智能系统全国重点实验室_智能机器人系统研究 |
通讯作者 | Junfeng Fan |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.Northwestern Polytechnical University 3.Yaskawa Shougang Robot Co., Ltd. |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yunkai Ma,Junfeng Fan,Huizhen Yang,et al. An Efficient and Robust Complex Weld Seam Feature Point Extraction Method for Seam Tracking and Posture Adjustment[J]. IEEE Transactions on Industrial Informatics,2023,19(11):10704 - 10715. |
APA | Yunkai Ma.,Junfeng Fan.,Huizhen Yang.,Hongliang Wang.,Shiyu Xing.,...&Min Tan.(2023).An Efficient and Robust Complex Weld Seam Feature Point Extraction Method for Seam Tracking and Posture Adjustment.IEEE Transactions on Industrial Informatics,19(11),10704 - 10715. |
MLA | Yunkai Ma,et al."An Efficient and Robust Complex Weld Seam Feature Point Extraction Method for Seam Tracking and Posture Adjustment".IEEE Transactions on Industrial Informatics 19.11(2023):10704 - 10715. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
An Efficient and Rob(9580KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论