• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.363-375
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• 2013

Today, a shortage of the skilled operator has been intensified gradually and the necessity of an earthwork in extreme environment operators are difficult to access is increasing for the purpose of resource development and new living space creation. For this reason, an effort to develop an unmanned excavation robot for fully automated earthwork system is continuing globally. In Korea, a research consortium called 'Intelligent Excavation System' has been formed since 2006 as a part of Construction Technology Innovation Program of Ministry of Land, Transport and Maritime Affairs of Korea. Among detailed technologies of the Task Planning System is one of the core technologies of IES, this paper explains research and development process of the Local Area Design Module, which provides informatization unit to create automated excavators' work command information at operation level such as location, range, target, and sequence for excavation work. Designing of Local Area should be considered various influential factors such as excavator's specification, working mechanism, heuristics, and structural stability to create work plan guaranteed safety and effectiveness. For this research, conceptual and detail design of the Local Area is performed for analyzing design element and variable, and quantization method of design specification corresponding with heuristics and structural safety is generated. Finally, module is developed through constructed algorithm and developed module is verified.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.63-71
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• 2011

Pattern recognition of a cucumber were conducted to detect directly the binary images by using thresholding method, which have the threshold level at the optimum intensity value. By restricting conditions of learning pattern, output patterns could be extracted from the same and similar input patterns by the algorithm. The algorithm of pattern recognition was developed to determine the position of the cucumber from a real image within working condition. The algorithm, designed and developed for this project, learned two, three or four learning pattern, and each learning pattern applied it to twenty sample patterns. The restored success rate of output pattern to sample pattern form two, three or four learning pattern was 65.0%, 45.0%, 12.5% respectively. The more number of learning pattern had, the more number of different out pattern detected when it was conversed. Detection of feature pattern of cucumber was processed by using auto scanning with real image of 30 by 30 pixel. The computing times required to execute the processing time of cucumber recognition took 0.5 to 1 second. Also, five real images tested, false pattern to the learning pattern is found that it has an elimination rate which is range from 96 to 98%. Some output patterns was recognized as a cucumber by the algorithm with the conditions. the rate of false recognition was range from 0.1 to 4.2%.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.836-850
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• 2009

Human posture recognition has attracted tremendous attention in ubiquitous environment, performing arts and robot control so that, recently, many researchers in pattern recognition and computer vision are working to make efficient posture recognition system. However the most of existing studies is very sensitive to human variations such as the rotation or the translation of body. This is why the feature, which is extracted from the feature extraction part as the first step of general posture recognition system, is influenced by these variations. To alleviate these human variations and improve the posture recognition result, this paper presents 3D Star Skeleton and Principle Component Analysis (PCA) based feature extraction methods in the multi-view environment. The proposed system use the 8 projection maps, a kind of depth map, as an input data. And the projection maps are extracted from the visual hull generation process. Though these data, the system constructs 3D Star Skeleton and extracts the rotation invariant feature using PCA. In experimental result, we extract the feature from the 3D Star Skeleton and recognize the human posture using the feature. Finally we prove that the proposed method is robust to human variations.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.9-17
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• 2017

This study was conducted in 241 fire officers at fire stations in Daejeon Metropolitan City to determine their oral health care behavior status and obtained the following results: First, men were more likely to brush their teeth 3 times a day and women were more likely to brush their teeth 4 times a day; those who were in their twenties and had ${\leq}5$ years of career brushed their teeth for ${\geq}3$ minutes. Second, the respondents who were in their twenties and thirties and had <10 years of career were more likely to use auxiliary oral hygiene devices and fire captains and those at higher positions were more likely to have received oral health education. Third, the respondents having received oral health education were more likely to use auxiliary oral hygiene devices and to have their teeth scaling within a year. While the fire officers were fortunately at good levels of oral health care, taking the poor working environment into account, the efforts to develop job-customized oral health programs in which IT and robot technologies are combined to improve oral health and take measures to publicize the programs and to give better treatment to fire officers are expected to put them in better oral health care status.

• Journal of Bio-Environment Control
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• v.13 no.1
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• pp.1-7
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• 2004

This study is kinematics for the manipulator development of cucumber harvesting. A theory value was verified by repeated error measurement after the forward kinematics or inverse kinematics analysis of manipulator. Manipulator is consisted of one perpendicular link and two revolution link. The transformation of manipulator can be valued by kinematics using Denavit-Hartenberg parameter. The value of inverse kinematics which is solved by three angles faction shows two types. Repeated errors refered maximum 2.60 mm, 2.05mm and 1.55 mm according to X, Y, Z axis. In this study, the actual coordinates of maximum point and minimum point were agreement in the forward kinematics or inverse kinematics. The results of repeated error measurement were reflect to be smaller compared to a diameter of cucumber. measurement errors were determined by experimented errors during the test. For reducing errors of manipulator and improving work efficiency, the number of link should be reduced and breeding and cultural environment should be considered to reduce the weight and use the hard stuff. The velocity of motor for working should be considered, too.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

• Information Systems Review
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• v.21 no.4
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• pp.143-156
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• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).