Autonomous mobile welding robot for discontinuous weld seam recognition and tracking

Author(s):  
Liang Guo ◽  
Hua Zhang
2010 ◽  
Vol 15 (4) ◽  
pp. 374-385 ◽  
Author(s):  
Namkug Ku ◽  
Ju-hwan Cha ◽  
Kyu-Yeul Lee ◽  
Jongwon Kim ◽  
Tae-wan Kim ◽  
...  

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.


2013 ◽  
Vol 303-306 ◽  
pp. 1678-1684
Author(s):  
Xian Chun Meng ◽  
Kai Li ◽  
Dong Mei Zhang ◽  
Jian Hu Zuo ◽  
Yan Jun Li

The dynamics equation of mobile welding robot is established. In controller design of the mobile welding robot, the non-holonomic constraint is introduced that limits the size of the transverse sliding and avoid the coordinates of the instantaneous center of rotation is larger than the wheelbase, to ensure the robot’s stability. Based on kinematics oscillator, the effect of uncertain dynamic parameters is considered. According to the Lyapunov stability criterion, the control algorithm is deduced. Simulating results by MATLAB software shows that the design of the control algorithm is stable, convergent and effective.


Author(s):  
Qing Tang

Purpose – The purpose of this paper is to design the localization and tracking algorithms for our mobile welding robot to carry out the large steel structure welding operations in industrial environment. Design/methodology/approach – Extended Kalman filter, considering the bicycle-modeled robot, is adopted in the localization algorithm. The position and orientation of our mobile welding robot is estimated using the feedback of the laser sensor and the robot motion commands history. A backstepping variable is involved in the tracking algorithm. By introducing a specifically selected Lyapunov function, we proved the tracking algorithm using Barbalat Lemma, which leads the errors of estimated robot states to converge to zero. Findings – The experiments show that the proposed localization method is fast and accurate and the tracking algorithm is robust to track straight lines, circles and other typical industrial curve shapes. The proposed localization and tracking algorithm could be used, but not limited to the mobile welding. Originality/value – Localization problem which is neglected in previous research is very important in mobile welding. The proposed localization algorithm could estimate the robot states timely and accurately, and no additional sensors are needed. Furthermore, using the estimated robot states, we proposed and proved a tracking algorithm for bicycle-modeled mobile robots which could be used in welding as well as other industrial operation scenarios.


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