• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.251-256
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• 2007

FY-2C 위성은 2004년 10월 발사되어 동경 105도 에 서 운영 중인 중국의 정지 궤도 기상위성 이며 관측 영상은 한반도 지역을 포함하고 있다. 현재 FY-2C S-VISSR2.0[l]에 대한 Navigation 알고리즘이 공개되어 있지 않으며，Navigation을 위하여 S-VISSR2.0에 포함되어 있는 Simplified Mapping Block 정보를 사용하여야 한다. Simplified Mapping Block은 5도 간격의 정보만을 제 공하므로 관측 지 역 의 모든 좌표에 대한 Navigation 정보를 얻기 위해서는 보간볍을 사용하여야 한다. 그러나 보간법은 기준 점에서 멀어질수록 오차가 크게 나타날 수 있다. 따라서 본 논문에서는 모든 좌표에 대한 Navigation 정보를 얻을 수 있는 MTSAT Image Navigation 알고리즘을 FY-2C S-VISSR2.0에 적용하여 Simplified Mapping Block과의 차이를 분석하였다. 분석 방법은 Simplified Mapping Block과 MTSAT Image Navigation[2] 알고리즘을 5도 간격의 격자 점(위경도)에서 Column 및 Line 값 비교， Geo-location된 영상의 품질 비교，WDB2 Map Data의 Coast Line과의 비교를 수행하였다. 분석 결과 격자 점에서의 Column, Line 값은 0.5 이내의 차이 값을 나타내었다. 그리고 Geo-location된 영상 비교에서는 격자 점 주변에서 영상의 차이가 없으나 격자 점에서 멸어질수록 영상의 품질은 MTSAT Image Navigation 알고리즘으로 생성한 영상이 더 우수하였다. WDB2 Map Data의 Coast Line과의 비교에서 오차는 동일하게 발생하였으며，영상의 Column 축에 대한 오차는 평균 1.847 Pixel, 최대 6 Pixel, 최소 oPixel 이며， Line 축에 대한 오차는 평균 0.135 Pixel, 최대 4 Pixel, 최소 0 Pixel을 나타내었다.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.982-988
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• 2006

The errors of INS (Inertial Navigation System) are known to grow in time. To compensate the accumulated errors, measurements of external or onboard sensors are extensively utilized to form an integrated navigation system. Recently, INS/GPS integrated navigation systems have become popular since exact position and velocity information can be utilized by low cost GPS receivers. Unfortunately, this configuration cannot be trusted at all times especially when there are intentional or unexpected jammings and interruptions. To aid INS irrespectively of these cases, an INS/Image sensor integrated navigation system configuration is designed only based on the information of image sensor gimble angles. The performance of the INS/Image sensor integrated navigation system is evaluated by Monte Carlo simulation.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.327-333
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• 2007

We propose a navigation algorithm using image-based visual servoing utilizing a fixed camera. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the image error between the goal position and the position of a mobile robot. The residual function which is the image error between the position of a mobile robot and the goal position is generally large for this navigation problem. So, this navigation problem can be considered as the nonlinear least squares problem for the large residual case. For large residual, we propose a method to find the second-order term using the secant approximation method. The performance was evaluated using the simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.245-246
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• 2014

This paper suggests the navigation information display system which is based on augmented reality technology and especially focuses on image analysis technology. Navigator has to always confirm the information from marine electronic navigation devices and then they compare with the view of outside targets of the windows. During this 'head down' posture, they feel uncomfortable and sometimes it cause near-accidents such as collision or missing objects, because he or she cannot keep an eye on the front view of windows. Augmented reality can display both of information of virtual and real in a single display. Therefore we tried to adapt the AR technology to help navigators and have been studied and developed image pre-processing module as a previous research already. To analysis the outside view of the bridge window, we have extracted navigational information from the camera image by using image processing. This paper mainly describes about recognizing ship feature by haar-like feature and filtering region of interest area by AIS data, which are to improve accuracy of the image analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.674-680
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• 2010

It is known that many insects and animals can return to their nest after exploration, with their own specific homing mechanisms. Their homing navigation methods have been applied to the robotic navigation. In this paper, we test the sector-based image matching method motivated by the honeybee's landmark navigation behaviour. Here, our robotic approach uses the reference compass to identify the current head direction and the relative angular position of landmarks for the navigation. The robot shows desirable homing behaviors if the robot is surrounded by landmarks. The result of robot experiment is in good agreement with that of simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.429-434
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• 2005

In this paper, the maze navigation system using image recognition for autonomous mobile robot is proposed. The proposed maze navigation system searches the target by image recognition method based on ADALINE neural network. The infrared sensor system must travel all blocks to find target because it can recognize only one block information each time. But the proposed maze navigation system can reduce the number of traveling blocks because of the ability of sensing several blocks at once. Especially, due to the simplicity of the algorithm, the proposed method could be easily implemented to the system which has low capacity processor.

• Journal of the Korean Institute of Navigation
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• v.19 no.3
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• pp.21-28
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• 1995

Mathematical morphology skeleton image processing makes many partial skeleton image planes from an original binary image. And the original binary image can be reconstructed without any distortion by summing the first partial skeleton image plane and each dilated partial skeleton image planes using the same structuring element. Especially compression effects of Elias coding to the morphological globally minimal skeleton(GMS) image, is better than that of PCX and Huffman coding. And then this paper proposes mathematical morphological GMS image processing which can be applied to a binary image transmitting for facimile and big size(bigger than $64{\times}64$ size) bitmap fonts storing in a memory.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2498-2504
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• 2009

The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We propose an image-based visual servo navigation algorithm for a wheeled mobile robot utilizing a ceiling mounted camera. For the image-based visual servoing, we define the composite image Jacobian which represents the relationship between the speed of wheels of a mobile robot and the robot's overall speed in the image plane. The rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot in the image plane using the composite image Jacobian. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the image error between the goal position and the position of a mobile robot. In order to avoid the obstacle, the modified cost function is proposed which is composed of the image error between the position of a mobile robot and the goal position and the distance between the position of a mobile robot and the position of the obstacle. The performance was evaluated using the simulation.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.447-451
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• 2011

Recently, various in-vehicle networks have been developed respectively in order to accomplish their own purposes such as CAN and MOST. Especially, the MOST network is usually adapted to provide entertainment service. The car navigation system is also widely used for guiding driving paths to driver. The position for the navigation system is usually acquired by GPS technology. However, the GPS technique has two serious problems. The first is unavailability in urban canyons. The second is inherent positional error rate. The problems have been studied in many literatures. However, the second still leads to incorrect locational information in some area, especially parallel roads. This paper proposes a performance tuning method of image matching algorithm for the car navigation system. The method utilizes images obtained from in-vehicle MOST network and a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. In order to accuracy improvement of image matching algorithm, three conditions are applied. The experimental tests show that the proposed system increases the accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.274-282
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• 2019

Vision-based navigation of unmaned aerial vehicle is a significant technology that can reinforce the vulnerability of the widely used GPS/INS integrated navigation system. However, the existing image matching algorithms are not suitable for matching the aerial image with the database. For the reason, this paper proposes particle filters using Gaussian mixture models to deal with matching between aerial image and database for vision-based navigation. The particle filters estimate the position of the aircraft by comparing the correspondences of aerial image and database under the assumption of Gaussian mixture model. Finally, Monte Carlo simulation is presented to demonstrate performance of the proposed method.