• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.213-218
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• 2003

The equipment of industrial robot in manufacturing and assembly lines has rapidly increased. In order to achieve high productivity and flexibility, it becomes very important to develop the visual feedback control system with Off-Line Programming System(OLPS). We can save much efforts and time in adjusting robots to newly defined workcells by using OLPS. A proposed visual calibration scheme is based on position-based visual feedback. The calibration program firstly generates predicted images of objects in an assumed end-effector position. The process to generate predicted images consists of projection to screen-coordinates, visible range test and construction of simple silhouette figures. Then camera images acquired are compared with predicted ones for updating position and orientation data. Computation of error is very simple because the scheme is based on perspective projection which can be also expanded to experimental results. Computation time can be extremely reduced because the proposed method does not require the precise calculation of tree-dimensional object data and image Jacobian.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.874-879
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• 1992

It is shown that there exists a nonlinear mappping which transforms features and their changes to the desired camera motion without measurement of the relative distance between the camera and the part, and the nonlinear mapping can eliminate several difficulties encountered when using the inverse of the feature Jacobian as in the usual feature-based visual feedback controls. And instead of analytically deriving the closed form of such a nonlinear mapping, a fuzzy membership function (FMF) based neural network is then proposed to approximate the nonlinear mapping, where the structure of proposed networks is similar to that of radial basis function neural network which is known to be very useful in function approximations. The proposed FMF network is trained to be capable of tracking moving parts in the whole work space along the line of sight. For the effective implementation of proposed IMF networks, an image feature selection processing is investigated, and required fuzzy membership functions are designed. Finally, several numerical examples are illustrated to show the validities of our proposed visual servoing method.

• 한국기계가공학회지
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• 제12권1호
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• pp.35-42
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• 2013

This paper proposes a new approach to the designed of visual feedback control system based on visual servoing method. The main focus of this paper is presented how it is effective to use many features for improving the accuracy of the visual feedback control of industrial articulated robot for assembling and inspection of parts. Some rank conditions, which relate the image Jacobian, and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. The effectiveness of redundant features is verified by the real time experiments on a SCARA type robot(FARA) made in samsung electronics company.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.559-564
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• 1994

Recently, a visual servoing for an eye-in-hand robot has become an interesting problem. A distance between a camera and a task object is very useful information for visual servoing. In the previous works for visual servoing, the distance can be obtained from the difference between a reference and a measured feature value of the object such as area on image plane. However, since this feature depends on the object, the reference feature value must be changed when other task object is taken. To overcome this difficulty, this paper presents a novel method for visual servoing. In the proposed method, a blur is used to obtain the distance. The blur, one of the most important features, depends on the focal length of camera. Since it is not affected by the change of object, the reference feature value is not changed although other task object is taken. In this paper, we show a relationship between the distance and the blur, and define the feature jacobian matrix based on camera defocusing to operate the robot. A series of experiments is performed to verify the proposed method.

• 대한자원환경지질학회:학술대회논문집
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• 대한자원환경지질학회 2002년도 춘계 공동학술발표회
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• pp.163-166
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• 2002

Initial velocity model close to real velocity structure of the subsurface governs the quality of image of prestack depth migration. Geophysicists employ velocity estimation tools such as velocity analysis (curvature method, coherency inversion), tomography and waveform inversion. We present a reflection tomography that parameterizes the subsurface into the movable blocks. By interpreting the depth-migrated section or stacked section, we can design an initial constant velocity model having only impedance boundaries. We use shooting-raytracing method that allows us to calculate the Jacobian-matrix efficiently.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권1호
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• pp.41-47
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• 2000

A better tracking performance can be achieved, if visual sensors such as CCD cameras are used in controling a robot manipulator, than when only relative sensors such as encoders are used. However, for precise visual servoing of a robot manipulator, an expensive vision system which has fast sampling rate must be used. Moreover, even if a fast vision system is implemented for visual servoing, one cannot get a reliable performance without use of robust and stable inner joint servo-loop. In this paper, we propose a dynamic control scheme for robot manipulators with eye-in-hand camera configuration, where a dynamic learning controller is designed to improve the tracking performance of robotic system. The proposed control scheme is implemented for tasks of tracking moving objects and shown to be robust to parameter uncertainty, disturbances, low sampling rate, etc.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2995-2997
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• 1999

Recently, real-time visual tracking control for a robot manipulator is performed by using a vision feedback sensor information. In this paper, the optical flow is computed based on the eye-in-hand robot configuration. The image jacobian is employed to calculate the rotation and translation velocity of a 3D moving object. LQG visual controller generates the real-time visual trajectory. In order to improving the visual tracking performance. VSC controller is employed to control the robot manipulator. Simulation results show a better visual tracking performance than other method.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (1)
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• pp.343-345
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• 2002

본 논문은 차원이 큰 행렬 연산 때문에 많은 계산 시간을 필요로 하는 ET 영상 복원 응용의 속도를 개선하기 위하여 3 대의 PC로 구성된 클러스터를 구축하고 복원 과정 중 가장 많은 시간을 차지하는 자코비언 행렬 계산에 대해 병렬 계산 기법을 제시한다. 각 노드는 리눅스 운영체제, MPI, 산술 계산 라이브러리 등을 탑재하여 C 언어로 옹용이 작성될 수 있으며 자코비언 행렬은 각 계산 루프의 데이터 독립성이 강하므로 병렬 계산의 장점을 최대화 할 수 있다. 구현된 클러스터 자코비언 프로그램은 주어진 인자를 분석하여 MPI 프리미티브에 의해 각각의 노드에 분배시키고 각 노드들로 하여금 자신의 계산 라이브러리를 이용하여 계산하게 한 다음 이 부분 결과를 모아 최종적인 자코비언 행렬을 생성한다. 이 프로그램을 클러스터에서 수행시키고 그 수행시간을 측정한 결과 기존의 자코비언 프로그램에 비해 최대 40% 까지 수행시간을 단축시킬 수 있었으며 추후 행렬의 차원이 증가할 경우 클러스터 컴퓨팅에 의한 성능 개선을 기할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.238-243
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• 1998

This paper presents a new approach to visual servoing with the stereo vision. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using a binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method fur a SCARA robot.

• 전기전자학회논문지
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• 제19권2호
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• pp.219-224
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• 2015

전기 임피던스 단층촬영 기법은 전극들을 통해 전류를 주입하고 이에 유기되는 전압을 측정한 후, 이들 데이터를 기반으로 내부의 도전율 분포를 영상으로 복원하는 방법이다. 이 논문에서는 기존의 Gauss-Newton 방법의 역행렬 항목의 차원을 도메인의 원소의 개수가 아닌 데이터의 개수의 차원으로 바꿔줌으로써, 관심 도메인 내부의 도전율 분포를 보다 빠르게 추정할 수 있는 방법을 제안하였다. 그리고 자코비안 행렬의 대각성분의 최소-최대를 이용하여 조정인자를 계산하는 방법을 함께 제안하였다. 몇 가지 시나리오를 설정하고 모의실험을 통해 제안한 방법의 복원 성능을 비교분석하였다.