Robotic Curve-Shaped Seam Tracking System Using Vision Sensor

2013 ◽  
Vol 397-400 ◽  
pp. 1486-1489
Author(s):  
Feng Xin Gao
Keyword(s):  
Image Processing ◽  
Fuzzy Controller ◽  
Tracking System ◽  
Processing Method ◽  
Seam Tracking ◽  
Feature Points ◽  
Vision Sensor ◽  
End Effector ◽  
Tuning Mechanism ◽  
Self Tuning

This paper presents a vision-based curve-shaped seam tracking system. The measurement of the curve trajectory is based on a camera that is installed ahead of the end effector of the robot. Effective image processing method is designed to extract the feature points of the curve. Then a fuzzy controller is proposed to control the position of the robot to track the curve. To improve the performance of the controller, a self-tuning mechanism is added to the controller. Finally, experiments are fully conducted to verify the effectiveness of the proposed method.

Research on the High-Speed Object Shadowgraph Image Processing Method Based on Adaptive Threshold Segmentation

2013 ◽  
Vol 325-326 ◽  
pp. 1571-1575
Author(s):  
Fang Wang ◽  
Zong Wei Yang ◽  
De Ren Kong ◽  
Yun Fei Jia
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Center Of Mass ◽  
Image Data ◽  
Ccd Camera ◽  
Adaptive Threshold ◽  
Processing Method ◽  
Laser Source ◽  
Feature Points ◽  
Threshold Segmentation

Shadowgraph is an important method to obtain the flight characteristics of high-speed object, such as attitude and speed etc. To get the contour information of objects and coordinates of feature points from shadowgraph are the precondition of characteristics analysis. Current digital shadowgraph system composed of CCD camera and pulsed laser source is widely used, but still lack of the corresponding method in image processing. Therefore, the selection of an effective processing method in order to ensure high effectiveness and accuracy of image data interpretation is an urgent need to be solved. According to the features of shadowgraph, a processing method to realize the contour extraction of high-speed object by adaptive threshold segmentation is proposed based on median filtering in this paper, and verified with the OpenCV in VC environment, the identification process of the feature points are recognized. The result indicates that by using this method, contours of high-speed objects can be detected nicely, to combine relevant algorithm, the pixel coordinates of feature points such as the center of mass can be recognized accurately.

Recognition and Tracking of Large Seam Based on Robotic Vision

2000 ◽  
Author(s):  
Hong Yue ◽  
Lixin Sun ◽  
Kai Li ◽  
Jianru Shi
Keyword(s):  
Image Processing ◽  
Tracking System ◽  
Seam Tracking ◽  
Welding Quality ◽  
Large Structure ◽  
The Real ◽  
Robotic Vision ◽  
Weld Joints ◽  
Image Segment

Abstract For the seams of large Structure, the low accordance of joint openings usually results in displacement of the real welding track from the robot teaching track, which will affect the welding quality of the structure. It has very important meanings to apply robotic vision for recognizing the feature parameters of the weld joints. A set of seam tracking system is presented. In order to remove arc noise, the methods of LOG filter and image segment filter are used in image processing.

A Study on Modified Hough Algorithm for Image Processing in Weld Seam Tracking System

2015 ◽  
Vol 1088 ◽  
pp. 824-828 ◽  
Author(s):  
Jong Pyo Lee ◽  
Qian Qian Wu ◽  
Min Ho Park ◽  
Cheol Kyun Park ◽  
Ill Soo Kim
Keyword(s):  
Image Processing ◽  
Weld Seam ◽  
Gma Welding ◽  
Vision System ◽  
Tracking System ◽  
Computing Time ◽  
Weld Line ◽  
Welding Process ◽  
Seam Tracking ◽  
Weld Seam Tracking

In modern market, achieving mechanical and automatic arc welding process is the key issue to be solved in welding industries. Because of the high complexity of the welding environment, manual detection of the weld line information is hard to be successful and time consuming. Therefore, this study aim at developing a new image processing algorithm for seam tracking system in Gas Metal Arc (GMA) welding by modified Hough algorithm based on the laser vision system. Firstly, noises in the captured weld seam images by CCD camera were effectively removed by noise filtering algorithm and then weld joint position were detected by the modified Hough algorithm to realize the automatic weld seam tracking. To verify the efficiency of the developed image processing model, a common image processing method was employed and the processed results were compared with the proposed algorithm. Statistical results proved that the modified Hough algorithm was able to acquire the weld information precisely with less computing time and memory cost, which also capable for industrial application.

Study on Weld Seam Tracking System Based on Laser Vision Sensing

2013 ◽  
Vol 655-657 ◽  
pp. 1108-1113 ◽  
Author(s):  
Ming Qiang Cao ◽  
Zhi Hong Yan ◽  
Yong Lun Song ◽  
Zhi Xiang Chen
Keyword(s):  
Tracking System ◽  
Seam Tracking ◽  
Vision Sensor ◽  
Tracking Errors ◽  
Visual Sensing ◽  
System A ◽  
Sensing Technology ◽  
Weld Seam Tracking ◽  
Laser Vision ◽  
Contact Sensor

Seam tracking is a basic condition to ensure a fine welding shape. In order to meet this requirement, the researchers have put forward a variety of sensors and some of them have been applied to practice successfully, such as contact sensor, arc sensor and vision sensor. Laser vision sensor has been proven to be one of the most successfully technology for its many advantages. In this paper, based on laser visual sensing technology, a seam tracking system is established with an embedded microcontroller LPC1768. With this system, a real-time tracking algorithm is proposed and the seam tracing process is realized under a smaller error. Finally, the tracking errors resources and their influence have been simulated and analyzed.

A Study on Image Processing Algorithms for Seam Tracking System in GMA Welding

2015 ◽  
Vol 1088 ◽  
pp. 819-823
Author(s):  
Min Ho Park ◽  
Qian Qian Wu ◽  
Cheol Kyun Park ◽  
Jong Pyo Lee ◽  
Ill Soo Kim
Keyword(s):  
Image Processing ◽  
Gma Welding ◽  
Tracking System ◽  
Ccd Camera ◽  
Cost Effective ◽  
Seam Tracking ◽  
Image Process ◽  
Laser Vision Sensor ◽  
Laser Vision ◽  
Welded Seam

With the development of economy, the seam tracking technology for arc welding becomes one of the major research tasks in the manufacturing area with robots. In this study, the objectives aim to develop an intelligent and cost-effective algorithm based on the laser vision sensor for image processing in Gas Metal Arc (GMA) welding. Images of welded seam were captured from the CCD camera. These images were then processed by the algorithms in the proposed image processing. To optimize the effective image process, popular algorithms in use were verified, compared and finally selected for every step in the image processing. Moreover, owing to the simple interactive environment and abundant toolboxes, MATLAB was employed to realize those algorithms, which offer a sample for engineers to achieve the goal of algorithm developed by this new but easier approach. Finally, weld seam images obtained with different welding environments were processed to enhance the proposal validity, and it’s proved to have significant effect of getting rid of the variable noises to extract the feature points and centerline for seam tracking in GMA welding and is capable for industrial application.

A seam tracking system based on a laser vision sensor

Measurement ◽  
2018 ◽  
Vol 127 ◽  
pp. 489-500 ◽  
Author(s):  
Yanbiao Zou ◽  
Xiangzhi Chen ◽  
Guoji Gong ◽  
Jinchao Li
Keyword(s):  
Tracking System ◽  
Seam Tracking ◽  
Vision Sensor ◽  
Laser Vision Sensor ◽  
Laser Vision
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