• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.312-321
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• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.828-834
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• 2013

In this paper, TMC (Tracker Motion Controller) as one of the many research methods for condensing efficiency improvements can be condensed into efficient solar system configuration to improve the power generation efficiency of the castle with Concentrated solar silicon and photovoltaic systems (CPV)experiments using PV systems. Microprocessor used on the solar system, tracing the development of solar altitude and latitude of each is calculated in real time. Also accept the value from the sensor, motor control and communication with the central control system by calculating the value of the current position of the sun, there is a growing burden on the applicability. Through the way the program is appropriate for solar power systems and sensors hybrid-type algorithm was implemented in the ARM core with built-in TMC, Concentrated CPV system compared to the existing PV systems, through the implementation of the TMC in the country's power generation efficiency compared and analyzed. Sensor method using existing experimental results Concentrated solar power systems to communicate the value of GPS location tracking method hybrid solar horizons in the coordinate system of the sun's azimuth and elevation angles calculated by the program in the calculations of astronomy through experimental resultslook clear day at high solar irradiation were shown to have a large difference. Stopped after a certain period of time, the sun appears in the blind spot of the sensor, the sensor error that can occur from climate change, however, do not have a cloudy and clear day solar radiation sensor does not keep track of the position of the sun, rather than the sensor of excellence could be found. It is expected that research is constantly needed for the system with ongoing research for development of solar cell efficiency increases to reduce the production cost of power generation, high efficiency condensing type according to the change of climate with the optimal development of the ability TMC.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.211-221
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• 2012

To utilize omni-directional images acquired by a rotating line camera for indoor spatial information services, we should register precisely the images with respect to an indoor coordinate system. In this study, we thus develop a georeferencing method to estimate the exterior orientation parameters of an omni-directional image - the position and attitude of the camera at the acquisition time. First, we derive the collinearity equations for the omni-directional image by geometrically modeling the rotating line camera. We then estimate the exterior orientation parameters using the collinearity equations with indoor control points. The experimental results from the application to real data indicate that the exterior orientation parameters is estimated with the precision of 1.4 mm and $0.05^{\circ}$ for the position and attitude, respectively. The residuals are within 3 and 10 pixels in horizontal and vertical directions, respectively. Particularly, the residuals in the vertical direction retain systematic errors mainly due to the lens distortion, which should be eliminated through a camera calibration process. Using omni-directional images georeferenced precisely with the proposed method, we can generate high resolution indoor 3D models and sophisticated augmented reality services based on the models.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.282-294
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• 2017

In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

• Korean Journal of Construction Engineering and Management
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• v.14 no.5
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• pp.35-43
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• 2013

Nowadays the widely used media in architecture include visualizations, animations and three-dimensional models. 3D digital methods using active CAM(Computer Aided Manufacturing) and CNC(Computerized Numerical Control) imaging have been developed for accurate shape and 3D measurements in freeform buildings. In contrast to a conventional building using auto CAD system and others, the proposed digital optimization method is based on a combination of 3D numerical data and parametric 3D model for design and construction. The objective of this paper is therefore to present digital optimization process for constructability of freeform building. The method can be useful in the effective implementation of an error-proofing process of freeform building during design and construction phase. 3D digital coordinate data can be used effectively to identify correct size of structural and finish members and installation location of each members in construction field. In addition, architects, engineers and contractors can evaluate design, materials, constructability and identify error-proofing opportunities. Other project participants can also include representatives from all levels of management, departments as well as workers and key subcontractors' personnel, if necessary. The 3D digital optimization process is therefore appropriate to serious variations in freeform shape. For future study, the developed digital optimization method is necessary to be carried out to verify the robustness and accuracy for constructability in construction field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.353-365
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• 2024

Rumen cannulation is a surgical technique used to collect rumen contents from ruminants. However, rumen cannulation surgery may potentially impact the composition of the rumen microbiota. This study aimed to examine the longitudinal alterations in the rumen microbiota composition of Hanwoo steers after cannulation surgery. In this study, eight Hanwoo steers were used; four steers underwent rumen cannulation surgery (cannulation group), while the remaining four were left intact (control group). Rumen samples were collected from all eight steers using the stomach tubing method on the day before surgery (day 0) and on postoperative days 1, 4, 7, 10, 14, 17, 21, 24, and 28, resulting in 80 samples (10 timepoints × 8 animals). The microbiota of all 80 samples were analyzed using 16S rRNA gene amplicon sequencing with Quantitative Insights into Microbial Ecology version 2 (QIIME2). There were no significant differences (p > 0.05) in all major phyla and most major genera representing at least 0.5% of total sequences across all 80 samples between the control and cannulation groups on the preoperative and postoperative days. However, while the alpha diversity indices did not differ (p > 0.05) between the two groups on the preoperative day, they significantly differed (p < 0.05) between the two groups on the postoperative days. Further, the overall microbial distribution based on both unweighted and weighted principal coordinate analysis plots significantly differed (p < 0.05) between the two groups on both the preoperative and postoperative days. Orthogonal polynomial contrasts indicated that major genera and microbial diversity in the cannulation group decreased following surgery but returned to their initial states by postoperative day 28. In conclusion, this study demonstrates that rumen cannulation surgery affects some major taxa and microbial diversity, suggesting that the rumen cannulation method can alter the composition of rumen microbiota in Hanwoo steers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.2
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• pp.117-131
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• 2007

Representation of building internal space is an active research area as the need for more geometrically accurate and visually realistic increases. 3 dimensional representation is common ground of research for disciplines such as computer graphics, architectural design and engineering and Geographic Information System (GIS). In many cases CAD plans are the starting point of reconstruction of 3D building models. The main objectives of building reconstruction in GIS applications are visualization and spatial analysis. Hence, CAD plans need to be preprocessed and edited to adapt to the data models of GIS SW and then georeferenced to enable spatial analysis. This study automated the preprocessing of CAD data using AutoCAD VBA (Visual Basic Application), and the processed data was topologically restructured for further analysis in GIS environment. Accuracy of georeferencing CAD data was also examined by comparing the results of coordinate transformation by using digital maps and GPS measurements as the sources of ground control points. The reconstructed buildings were then applied to visualization and network modeling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.1063-1076
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• 2017

To improve the productivity of the earthwork, a fleet management system for construction equipment was suggested in previous studies. But there were some gaps between theory and practice. To overcome this problem, some opinions are gathered form experts and field engineers and four improvements have been proposed and reflected in the system. First, the previous system consists of one hardware module, so it is hard to install it at a control office and construction equipment at the same time. The server module for the office and the mobile module for construction equipment are separately developed. Second, the transportation algorithm that is used in the previous system can generate shortest paths for the earthwork distribution, but embankment areas are not gathered. This situation leads to a decrease in compaction productivity. A modified algorithm for earthwork distribution is suggested. Third, the automated coordinate transformation is performed to show the position of construction equipment on the 3D terrain in real-time. Fourth, construction equipment groups should be formed in the initial stage of earthwork and the number of equipment of each groups should be changed by operation status and site environment. But this functions did not work properly in the previous system. This problem is corrected in the proposed system. The improvements can make the proposed system much more realistic one and can leads to an increase in the productivity of earthwork operations.