A novel seam extraction and path planning method for robotic welding of medium-thickness plate structural parts based on 3D vision

被引:62
作者
Geng, Yusen
Lai, Min
Tian, Xincheng [1 ]
Xu, Xiaolong [1 ]
Jiang, Yong
Zhang, Yuankai
机构
[1] Shandong Univ, Ctr Robot, Sch Control Sci, Jinan 250061, Peoples R China
基金
中国博士后科学基金;
关键词
3D vision; Multiplans fitting; Welding seam extraction; Welding path planning; Welding posture planning; VISUAL TRACKING; SYSTEM; ALGORITHM;
D O I
10.1016/j.rcim.2022.102433
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Currently, the robotic welding of medium-thickness plate structural parts has become a common welding application. With the rapid development of automation technology and robotics, the traditional teaching -playback mode and the off-line programming mode cannot meet the automation demand of welding robots. To realize automatic seam extraction and path planning for robotic welding of medium-thickness plate structural parts without programming and teaching, we use three models of medium-thickness plate structural parts as the research objects to propose a novel seam extraction and path planning method for robotic welding of medium-thickness plate structural parts based on 3D vision. Firstly, a set of improved RANSAC multiplanes fitting algorithms is proposed to accurately obtain the position of the intersection lines between the intersecting planes of the point cloud model. On this basis, we combine the geometric features of three models to propose the specific welding seam extraction methods respectively. Then, according to the spatial structure of the welding seams and the welding process, we carry out the welding path planning. Finally, a welding pose planning method based on the dihedral structure is proposed. Experiment results show that the proposed method can well realize the welding seam extraction, welding path and posture planning of medium-thickness plate structural parts without programming and teaching.
引用
收藏
页数:13
相关论文
共 34 条
[1]  
Ahmed SM, 2016, 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016), P2610, DOI 10.1109/IROS.2016.7759406
[2]   Exploring Infrared Sensoring for Real Time Welding Defects Monitoring in GTAW [J].
Alfaro, Sadek C. A. ;
Franco, Fernand Diaz .
SENSORS, 2010, 10 (06) :5962-5974
[3]   Toward superfast three-dimensional optical metrology with digital micromirror device platforms [J].
Bell, Tyler ;
Zhang, Song .
OPTICAL ENGINEERING, 2014, 53 (11)
[4]   Detection of fillet weld joints using an adaptive line growing algorithm for robotic arc welding [J].
Dinham, Mitchell ;
Fang, Gu .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2014, 30 (03) :229-243
[5]   Autonomous weld seam identification and localisation using eye-in-hand stereo vision for robotic arc welding [J].
Dinham, Mitchell ;
Fang, Gu .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2013, 29 (05) :288-301
[6]  
Fan CL, 2015, 2015 INTERNATIONAL CONFERENCE ON COMPUTERS, COMMUNICATIONS, AND SYSTEMS (ICCCS), P256, DOI 10.1109/CCOMS.2015.7562911
[7]   A Precise Initial Weld Point Guiding Method of Micro-Gap Weld Based on Structured Light Vision Sensor [J].
Fan, Junfeng ;
Jing, Fengshui ;
Yang, Lei ;
Long, Teng ;
Tan, Min .
IEEE SENSORS JOURNAL, 2019, 19 (01) :322-331
[8]   Automatic recognition system of welding seam type based on SVM method [J].
Fan, Junfeng ;
Jing, Fengshui ;
Fang, Zaojun ;
Tan, Min .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 92 (1-4) :989-999
[9]   Laser stripe peak detector for 3D scanners. A FIR filter approach [J].
Forest, J ;
Salvi, J ;
Cabruja, E ;
Pous, C .
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3, 2004, :646-649
[10]   Kalman Filtering Compensated by Radial Basis Function Neural Network for Seam Tracking of Laser Welding [J].
Gao, Xiangdong ;
Zhong, Xungao ;
You, Deyong ;
Katayama, Seiji .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2013, 21 (05) :1916-1923