• Design & Manufacturing
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• v.14 no.2
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• pp.14-20
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• 2020

In OLED panel production process, it is necessary to cut a part of protective film as a preprocess for lighting inspection. The current method is to recognize only the fiducial mark of the cut-out panel. Bare Glass Cutting does not compensate for machining cumulative tolerances. Even though process defects still occur, it is necessary to develop technology to solve this problem because only the Align Mark of the panel that has already been cut is used as the reference point for alignment. There is a lot of defective lighting during panel lighting test because the correct protective film is not cut on the panel power and signal application pad position. In laser cutting process to remove the polarizing film / protective film / TSP film of OLED panel, laser processing is not performed immediately after the panel alignment based on the alignment mark only. Therefore, in this paper, we performed real time inspection which minimizes the mechanism tolerance by correcting the laser cutting path of the protective film in real time using Machine Vision. We have studied calibration algorithm of Vision Software coordinate system and real image coordinate system to minimize inspection resolution and position detection error and edge detection algorithm to accurately measure edge of panel.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1029-1035
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• 2013

This paper proposes a real time lane detection algorithm using LRF (Laser Range Finder) for autonomous navigation of a mobile robot. There are many technologies for safety of the vehicles such as airbags, ABS, EPS etc. The real time lane detection is a fundamental requirement for an automobile system that utilizes outside information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. By the vision-based system, recognition of environment for three dimensional space becomes excellent only in good conditions for capturing images. However there are so many unexpected barriers such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement. In this paper, we introduce a three dimensional lane detection algorithm using LRF, which is very robust against the illumination. For the three dimensional lane detections, the laser reflection difference between the asphalt and lane according to the color and distance has been utilized with the extraction of feature points. Also a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been verified through the real experiments.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.258-267
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• 1999

An intelligent safety vehicle(ISV) should have an ability to predict the possibility of an accident and help a driver avoid the accident in advance. The basic function of the ISV is to alert the driver by warning when the collision is to occur. For this purpose, the ISV has to function efficiently in sensing the environmental context. While image processing provides lane information, laser radar senses road obstacles including vehicles. By applying a simple clustering algorithm to radar signals, it is possible to obtain the vehicle information. Consequently, we can identify the existence of the vehicle of interest on my lane. The reliability of the sensing algorithm is evaluated by running on the highway with a test vehicle.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.317-318
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• 2007

One of the important factors of the autonomous mobile robot is to build a map for surround environment and estimate its localization. This paper suggests a sensor fusion method of laser range finder and monocular vision sensor for the simultaneous localization and map building. The robot observes the comer points in the environment as features using the laser range finder, and extracts the SIFT algorithm with the monocular vision sensor. We verify the improved localization performance of the mobile robot from the experiment.

• Journal of the Korean Society for Precision Engineering
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• v.4 no.3
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• pp.60-68
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• 1987

An optoelectronical method for in process monitoring of flank wear of cutting tools is presented. The method is based upon real-time vision technology in which the tool is illuminated by a beam of laser and then the image of wear zone is taken by a vidicon camera. The image is converted to a series of digital pixel data and processed through an algorithm specially developed for measurement of the wear land width. Detailed aspects of the prototype measurement system byilt for experiment are described, and test results are discussed. As conclusions, it is proved that the methods are effec- tive especially for-in situ application with a measuring accuracy of 0.01mm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.237-240
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• 2003

Gas turbines are extensively used in flight propulsion, electrical power generation, and other industrial applications. During its life span, a turbine blade is taken out periodically for repair and maintenance. This includes re-coating the blade surface and re-drilling the cooling holes/channels. A successful laser re-drilling requires the measurement of a hole within the accuracy of ${\pm}0.15mm$ in position and ${\pm}3^{\circ}$ in orientation. Detection of gas turbine blade/vane cooling hole position and orientation thus becomes a very important step for the vane/blade repair process. The industry is in urgent need of an automated system to fulfill the above task. This paper proposes approaches and algorithms to detect the cooling hole position and orientation by using a vision system mounted on a robot arm. The channel orientation is determined based on the alignment of the vision system with the channel axis. The opening position of the channel is the intersection between the channel axis and the surface around the channel opening. Experimental results have indicated that the concept of cooling hole identification is feasible. It has been shown that the reproducible detection of cooling channel position is with +/- 0.15mm accuracy and cooling channel orientation is with +/$-\;3^{\circ}$ with the current test conditions. Average processing time to search and identify channel position and orientation is less than 1 minute.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.493-504
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• 2007

This paper proposes a stereo vision-based forward obstacle detection and distance measurement method. In general, stereo vision-based obstacle detection methods in automotive applications can be classified into two categories: IPM (Inverse Perspective Mapping)-based and disparity histogram-based. The existing disparity histogram-based method was developed for stop-and-go applications. The proposed method extends the scope of the disparity histogram-based method to highway applications by 1) replacing the fixed rectangular ROI (Region Of Interest) with the traveling lane-based ROI, and 2) replacing the peak detection with a constant threshold with peak detection using the threshold-line and peakness evaluation. In order to increase the true positive rate while decreasing the false positive rate, multiple candidate peaks were generated and then verified by the edge feature correlation method. By testing the proposed method with images captured on the highway, it was shown that the proposed method was able to overcome problems in previous implementations while being applied successfully to highway collision warning/avoidance conditions, In addition, comparisons with laser radar showed that vision sensors with a wider FOV (Field Of View) provided faster responses to cutting-in vehicles. Finally, we integrated the proposed method into a longitudinal collision avoidance system. Experimental results showed that activated braking by risk assessment using the state of the ego-vehicle and measuring the distance to upcoming obstacles could successfully prevent collisions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.287-292
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• 2002

This paper presents a reverse engineering method for compound surfaces using vision system. A CNC machining center is used as a measuring station, which is equipped with slit beam generator and vision probe. Since obtained data using slit beam or laser scanner may have much data loss along the edge of compound surfaces, an algorithm is presented in this study to recover missing geometric data at such region. First, b-spline interpolation is applied to extract edge information of the surface, and as a next step, b-spline approximation is applied to recover the missing geometric data. Finally, b-spline skinning method is applied to regenerate the surface information. Appropriate simulation and experimental works are preformed to very the effectiveness of the proposed methods.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1051-1056
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• 2014

In this paper, we introduce an intelligent robotic arc welding system which exploits sensors like as LVS (Laser Vision Sensor), Hall effect sensor, voltmeter and so on. The use of industrial robot is saturated because of its own limitation, and one of the major limitations is that industrial robot cannot recognize the environment. Lately, sensor-based environmental awareness research of the industrial robot is performed actively to overcome such limitation, and it can expand application field and improve productivity. We classify the sensor-based intelligent arc welding robot system by the goal and the sensing data. The goals can be categorized into detection of a welding start point, tracking of a welding line and correction of a torch deformation. The Sensing data can be categorized into welding data (i.e. current, voltage and short circuit detection) and displacement data (i.e. distance, position). This paper covers not only the explanation of the each category but also its advantage and limitation.

• Journal of Biosystems Engineering
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• v.24 no.2
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• pp.159-166
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• 1999

A system to extract continuously the real 3-D geometric fearture information from 2-D image of an object, which is fed randomly via conveyor has been developed. Two sets of structured laser lightings were utilized. And the laser structured light projection image was acquired using the camera from the signal of the photo-sensor mounted on the conveyor. Camera coordinate calibration matrix was obtained, which transforms 2-D image coordinate information into 3-D world space coordinate using known 6 points. The maximum error after calibration showed 1.5 mm within the height range of 103mm. The correlation equation between the shift amount of the laser light and the height was generated. Height information estimated after correlation showed the maximum error of 0.4mm within the height range of 103mm. An interactive 3-D geometric feature extracting software was developed using Microsoft Visual C++ 4.0 under Windows system environment. Extracted 3-D geometric feature information was reconstructed into 3-D surface using MATLAB.