A study on the welding seam tracking by using Laser Vision Sensor

Author(s):  
Taewook Kim ◽  
Seungbeom Lee ◽  
Seunghwan Baek ◽  
Kwangsuck Boo
Author(s):  
Chao Liu ◽  
Hui Wang ◽  
Yu Huang ◽  
Youmin Rong ◽  
Jie Meng ◽  
...  

Abstract Mobile welding robot with adaptive seam tracking ability can greatly improve the welding efficiency and quality, which has been extensively studied. To further improve the automation in multiple station welding, a novel intelligent mobile welding robot consists of a four-wheeled mobile platform and a collaborative manipulator is developed. Under the support of simultaneous localization and mapping (SLAM) technology, the robot is capable of automatically navigating to different stations to perform welding operation. To automatically detect the welding seam, a composite sensor system including an RGB-D camera and a laser vision sensor is creatively applied. Based on the sensor system, the multi-layer sensing strategy is performed to ensure the welding seam can be detected and tracked with high precision. By applying hybrid filter to the RGB-D camera measurement, the initial welding seam could be effectively extracted. Then a novel welding start point detection method is proposed. Meanwhile, to guarantee the tracking quality, a robust welding seam tracking algorithm based on laser vision sensor is presented to eliminate the tracking discrepancy caused by the platform parking error, through which the tracking trajectory can be corrected in real-time. The experimental results show that the robot can autonomously detect and track the welding seam effectively in different station. Also, the multiple station welding efficiency can be improved and quality can also be guaranteed.


Measurement ◽  
2018 ◽  
Vol 127 ◽  
pp. 489-500 ◽  
Author(s):  
Yanbiao Zou ◽  
Xiangzhi Chen ◽  
Guoji Gong ◽  
Jinchao Li

2007 ◽  
Vol 21 (10) ◽  
pp. 1720-1725 ◽  
Author(s):  
K. Park ◽  
Y. Kim ◽  
J. Byeon ◽  
K. Sung ◽  
C. Yeom ◽  
...  

Author(s):  

An algorithm for tracking of the welded seams grooving by using a Kalman filter based on six characteristic points of the profile obtained using the RF627 laser vision sensor is proposed. In order to reduce the error in weld seams control, a multilayer neural network with a backpropagation algorithm is created to compensate for errors caused by colored noise when using the Kalman filter. Experimental results show that when the algorithm is applied, the error in tracking the trajectory of weld seams is reduced. Keywords tracking of weld seams; multilayer/multi-pass welding; Kalman filter; multilayer perceptron


2004 ◽  
Vol 270-273 ◽  
pp. 2332-2337 ◽  
Author(s):  
H. Lee ◽  
K. Sung ◽  
H. Park ◽  
Se Hun Rhee

Author(s):  

Laser sensors with various technologies used to track weld seams during welding operations are discussed in detail Laser vision sensors provide full automation of welding robotic systems and real-time process monitoring. Reasonable selection of the control system for a robotic welding system with laser vision is represented. Based on the analysis of the advantages and disadvantages, the practical application of laser vision sensors in the process of automatic welding is predicted. Keywords weld seam tracking; laser vision sensor; robotic welding; seam recognition; pre-processing of images; structure of the control system


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