• Title/Summary/Keyword: image singularity system

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Theoretical Investigation on the Singularity System to Represent Two Circular Cylinders in an Inviscid Flow

  • Lee, D.K.
    • International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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    • v.3 no.1
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    • pp.8-13
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    • 2000
  • The singularity system to represent two circular cylinders poised under different ambient flow fields is considered in the present research. The singularity system, being composed of a series of singularities, has to be truncated for numerical calculations. A rational criterion to determine how many terms of this series should be retained to maintain the prescribed accuracy is provided through analysis of the converging property of the series. A particular emphasis is put to how to deal with the discrete vortex model of a boundary layer, this possibility being the basis for the development of a tool to simulate vortex shedding from a structure composed of two circular cylinders. The principle to obtain the present singularity system can be applied to more-than-cylinders structure. Only th series become much more complex with increase of the number of cylinders.

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Orbit Determination Accuracy Improvement for Geostationary Satellite with Single Station Antenna Tracking Data

  • Hwang, Yoo-La;Lee, Byoung-Sun;Kim, Hae-Yeon;Kim, Hae-Dong;Kim, Jae-Hoon
    • ETRI Journal
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    • v.30 no.6
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    • pp.774-782
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    • 2008
  • An operational orbit determination (OD) and prediction system for the geostationary Communication, Ocean, and Meteorological Satellite (COMS) mission requires accurate satellite positioning knowledge to accomplish image navigation registration on the ground. Ranging and tracking data from a single ground station is used for COMS OD in normal operation. However, the orbital longitude of the COMS is so close to that of satellite tracking sites that geometric singularity affects observability. A method to solve the azimuth bias of a single station in singularity is to periodically apply an estimated azimuth bias using the ranging and tracking data of two stations. Velocity increments of a wheel off-loading maneuver which is performed twice a day are fixed by planned values without considering maneuver efficiency during OD. Using only single-station data with the correction of the azimuth bias, OD can achieve three-sigma position accuracy on the order of 1.5 km root-sum-square.

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Visual servoing based on neuro-fuzzy model

  • Jun, Hyo-Byung;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.712-715
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    • 1997
  • In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

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Panoramic Navigation using Orthogonal Cross Cylinder Mapping and Image-Segmentation Based Environment Modeling (직각 교차 실린더 매핑과 영상 분할 기반 환경 모델링을 이용한 파노라마 네비게이션)

  • 류승택;조청운;윤경현
    • Journal of KIISE:Computer Systems and Theory
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    • v.30 no.3_4
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    • pp.138-148
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    • 2003
  • Orthogonal Cross Cylinder mapping and segmentation based modeling methods have been implemented for constructing the image-based navigation system in this paper. The Orthogonal Cross Cylinder (OCC) is the object expressed by the intersection area that occurs when a cylinder is orthogonal with another. OCC mapping method eliminates the singularity effect caused in the environment maps and shows an almost even amount of area for the environment occupied by a single texel. A full-view image from a fixed point-of-view can be obtained with OCC mapping although it becomes difficult to express another image when the point-of-view has been changed. The OCC map is segmented according to the objects that form the environment and the depth value is set by the characteristics of the classified objects for the segmentation based modeling. This method can easily be implemented on an environment map and makes the environment modeling easier through extracting the depth value by the image segmentation. An environment navigation system with a full-view can be developed with these methods.

A study on the improvement of the robot motion control as a part of the integrated human and robot ergonomics (Integrated Human and Rob-ot Ergonomics의 측면에서 로보트의 동작제어 개선에 관한 연구)

  • 이순요;권규식;홍승권
    • Journal of the Ergonomics Society of Korea
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    • v.9 no.1
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    • pp.21-27
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    • 1990
  • Teaching Expert System/World Coordinate System(TES/WDS) was proposed to improve robot motion control. First, precise coordinate reading for getting the inherent data about position and posture of task objects was performed throgh the integrated image and fuzzy processing. Second, singularity and parameter limitation problems in getting the motion data about position and posture of robot in macro motion were solved by proposed geometric algorithm. Third, the unnecessary robot motion was also removed by the Robot Time and Motion (RTM) method and the Multi-Geometric Straight-Line Motion (MGSLM) method in micro motion. This results demonstrated reduction of the average teaching task time according to task order.

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Region Based Image Similarity Search using Multi-point Relevance Feedback (다중점 적합성 피드백방법을 이용한 영역기반 이미지 유사성 검색)

  • Kim, Deok-Hwan;Lee, Ju-Hong;Song, Jae-Won
    • The KIPS Transactions:PartD
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    • v.13D no.7 s.110
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    • pp.857-866
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    • 2006
  • Performance of an image retrieval system is usually very low because of the semantic gap between the low level feature and the high level concept in a query image. Semantically relevant images may exhibit very different visual characteristics, and may be scattered in several clusters. In this paper, we propose a content based image rertrieval approach which combines region based image retrieval and a new relevance feedback method using adaptive clustering together. Our main goal is finding semantically related clusters to narrow down the semantic gap. Our method consists of region based clustering processes and cluster-merging process. All segmented regions of relevant images are organized into semantically related hierarchical clusters, and clusters are merged by finding the number of the latent clusters. This method, in the cluster-merging process, applies r: using v principal components instead of classical Hotelling's $T_v^2$ [1] to find the unknown number of clusters and resolve the singularity problem in high dimensions and demonstrate that there is little difference between the performance of $T^2$ and that of $T_v^2$. Experiments have demonstrated that the proposed approach is effective in improving the performance of an image retrieval system.