• Journal of Welding and Joining
• /
• v.21 no.2
• /
• pp.102-110
• /
• 2003

A visual sensor consisted of polygonal mirror, laser, and CCD camera was proposed to measure the distance to the weld joint for recognizing the joint shape. To scan the laser beam of the sensor onto an object, 8-facet polygonal mirror was used as the rotating mirror. By locating the laser and the camera at axi-symmetrical positions around the mirror, the synchronized-scan condition could be satisfied even when the mirror was set to rotate through one direction continuously, which could remove the inertia effect of the conventional oscillating-mirror methods. The mathematical modelling of the proposed sensor with the optical triangulation method made it possible to derive the relation between the position of an image on the camera and the one of a laser light on the object. Through the geometrical simulation of the proposed sensor with the principal of reflection and virtual image, the optical path of a laser light could be predicted. The position and direction of the CCD camera were determined based on the Scheimpflug's condition to fit the focus of any image reflected from an object within the field of view. The results of modelling and simulation revealed that the proposed visual sensor could be used to recognize the weld joint and its vicinity located within the range of the field of view and the resolution. (Received February 19, 2003)

• Journal of Welding and Joining
• /
• v.22 no.6
• /
• pp.43-49
• /
• 2004

In this study, a visual sensor system which can detect I-butt weld joint with height variation and includes a seam tracking algorithm was investigated. Three-dimensional position of an object can be acquired by using the method of distance measurement, i.e., an optical trigonometry which results from the spatial relations between the camera, the object and the structured light by a visible laser. Effects of laser intensity and iris number for the image quality as well as object material were investigated for the optical system design. For the image processing, a region of interest is defined from the whole image and a line image of laser is drew by using the gray level difference in the image. From the drew laser line, the weld joint can be recognized in searching the biggest point position calculated from the central difference method. Through a series of welding experiments, a good tracking performance was confirmed under GMA welding.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2007.06a
• /
• pp.405-406
• /
• 2007

• International Journal of Korean Welding Society
• /
• v.3 no.2
• /
• pp.53-59
• /
• 2003

Visual inspection using laser vision sensor was proposed for fast and economic inspection and was verified experimentally. Welding is one of the most important manufacturing processes for automotive and electronics industries as well as heavy industries. The weld zone influences the reliability of the products. There are two kinds of weld inspection tests, destructive and non­destructive test. Even though the destructive test is much more reliable, the product should be destroyed, and hence the non­destructive test such as ultrasonic or X­ray test was used to overcome this problem. However, these tests are not used for real time inspection.

• Journal of the Korean Society for Precision Engineering
• /
• v.24 no.10
• /
• pp.64-74
• /
• 2007

Because of the size and environment in the shipbuilding process, the portable type robot is required for the automatic seam tracking. For this reason, the structure of laser sensor should be considered in the initial design step and the coordinate transformation between welding robot and laser sensor, which is joint finder, must be identified exactly and the real time tracking algorithm based on these consideration could be developed. In this research, laser displacement sensor in which its structure is laser beam's vertical projection, is developed to recognize the location of weld joint. In practical applications, however, images of weld joints are often degraded because of the surface specularity or spatter. To overcome the problem, the constrained joint finding algorithm is proposed. In the approach of coordinate conversion rule for the visual feedback control among welding torch, robot body and laser sensor is applied by the same reference point method. In the real time seam tracking algorithms we propose constrained sampling method which uses look ahead distance. The RLS(Recursive Least Square) filter is applied to obtain the smooth tracking path from the sensitive edge data. From the experimental results, we could see the possibility that the developed laser sensor with proposed processing algorithm and real time seam tracking method can be used as a welding under the shipbuilding condition.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.3
• /
• pp.277-282
• /
• 2011

This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area and robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.9
• /
• pp.179-185
• /
• 2001

In this study, a visual sensor system for weld seam tracking the I-butt weld joints in GMA welding was constructed. The sensor system consists of a CCD camera, a diode laser with a cylindrical lens and a band-pass-filter to overcome the degrading of image due to spatters and arc light. In order to obtain the enhanced image, quantitative relationship between laser intensity and iris number was investigated. Throughout the repeated experiments, the shutter speed was set at 1-milisecond for minimizing the effect of spatters on the image, and therefore most of the spatter trace in the image have been found to be reduced. Region of interest was defined from the entire image and gray level of searched laser line was compared to that of weld line. The differences between these gray levels lead to spot the position of weld joint using central difference method. The results showed that, as long as weld line was within $^\pm$15$^\circ$from the longitudinal straight fine, the system constructed in this study could track the weld line successful1y. Since the processing time reduced to 0.05 sec, it is expected that the developed method could be adopted to high speed welding such as laser welding.

• Journal of Welding and Joining
• /
• v.18 no.3
• /
• pp.60-67
• /
• 2000

In this study, we constructed a preview-sensing visual sensor system for weld seam tracking in GMA welding. The visual sensor consists of a CCD camera, a diode laser system with a cylindrical lens and a band-pass-filter to overcome the degrading of image due to spatters and/or arc light. To obtain weld joint position and edge points accurately from the captured image, we compared Hough transform method with central difference method. As a result, we present Hough transform method can more accurately extract the points and it can be applied to real time weld seam tracking. Image processing is carried out to extract straight lines that express laser stripe. After extracting the lines, weld joint position and edge points is determined by intersecting points of the lines. Although a spatter trace is in the image, it is possible to recognize the position of weld joint. Weld seam tracking was precisely implemented with adopting Hough transform method, and it is possible to track the weld seam in the case of offset angle is in the region of $\pm15^{\circ}$.

• International Journal of Korean Welding Society
• /
• v.1 no.2
• /
• pp.23-29
• /
• 2001

In this study, a preview-sensing visual sensor system is constructed far weld seam tracking in GMA welding. The visual sensor system consists of a CCD camera, a diode laser system with a cylindrical lens, and a band-pass-filter to overcome the degrading of image due to spatters and/or arc light. Among the image processing methods, Hough transform method is compared with the central difference method from a viewpoint of the capability for extracting the accurate feature position. As a result, it was revealed that Hough transform method can more accurately extract the feature positions and it can be applied to real time weld seam tracking. Image processing which includes Hough transform method is carried out to extract straight lines that express laser stripe. After extracting the lines, weld joint position and edge points are determined by intersecting the lines. Even though the image includes a spatter trace on it, it is possible to recognize the position of weld joint. Weld seam tracking was precisely implemented with adopting Hough transform method, and it is possible to track the weld seam in the case of offset angle is in the region of $\pm$ $15^{\circ}$.

• Journal of Welding and Joining
• /
• v.19 no.2
• /
• pp.208-214
• /
• 2001

In this study, we constructed a visual sensor system for weld seam tracking in real time in GMA welding. A sensor part consists of a CCD camera, a band-pass filter, a diode laser system with a cylindrical lens, and a vision board for inter frame process. We used a commercialized robot system which includes a GMA welding machine. To extract the weld seam we used a inter frame process in vision board from that we could remove the noise due to the spatters and fume in the image. Since the image was very reasonable by using the inter frame p개cess, we could use the simplest way to extract the weld seam from the image, such as first differential and central difference method. Also we used a moving average method to the successive position data or weld seam for reducing the data fluctuation. In experiment the developed robot system with visual sensor could be able to track a most popular weld seam. such as a fillet-joint, a V-groove, and a lap-joint of which weld seam include planar and height directional variation.