Development of a Multi-Scanning Laser Vision Sensor System to extract the Machining Start Point

Author(s):  
Ji-Woo Kim ◽  
Dae-Hyun Baek ◽  
Jae-Won Choi ◽  
Hyung-Soon Moon
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.


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

Author(s):  
Taewook Kim ◽  
Seungbeom Lee ◽  
Seunghwan Baek ◽  
Kwangsuck Boo

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

1989 ◽  
Vol 1 (4) ◽  
pp. 274-277
Author(s):  
Minoru Kimura ◽  
◽  
Osamu Yamada ◽  
Hidemi Takahashi ◽  
Hiroshi Naitoh

2013 ◽  
Vol 45 ◽  
pp. 1-12 ◽  
Author(s):  
Fuqiang Zhou ◽  
Bin Peng ◽  
Yi Cui ◽  
Yexin Wang ◽  
Haishu Tan

2013 ◽  
Vol 401-403 ◽  
pp. 895-898
Author(s):  
Sheng Gao ◽  
Yu Wang

This paper studies the dynamic modeling of weld seam by using the laser vision sensor in virtual environment (VE). By introducing virtual guide (VG), lowering operative difficulty and showing high security can be obtained. Template matching is used to recognize remote weld seam, and the uniform contour of V is defined to represent the features of remote seam. Cubic spline interpolation is employed to construct the continuous model of the seam.


1999 ◽  
Author(s):  
Luciano Bartolini ◽  
Andrea Bordone ◽  
Alberto Coletti ◽  
Mario Ferri De Collibus ◽  
Giorgio G. Fornetti ◽  
...  

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