• 제어로봇시스템학회논문지
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• 제6권6호
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• pp.462-470
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• 2000

This paper proposes a visual servoing method based on QR decomposition and disturbance observer. The QR decomposition factors the image feature Jacobian into a unitary matrix and an upper triangular matrix. And it is shown that several performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability can be improved for any general image feature Jacobian by QR decomposition and disturbance observer. To show the validity of the proposed approach, visual servoing with stereo vision is carried out for a Samsung FARAMAN 6-axis industrial robot manipulator.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.1327-1330
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• 2004

An underwater robotic system has been developed and applied to visual inspection of reactor vessel internals. The Korea Electric Power Robot for Visual Test (KeproVt) consists of an underwater robot, a vision processor-based measuring unit, a master control station and a servo control station. The robot guided by the control station with the measuring unit can be controlled to have any motion at any position in the reactor vessel with $\pm$1 cm positioning and $\pm$2 degrees heading accuracies with enough precision to inspect reactor internals. A simple and fast installation process is emphasized in the developed system. The developed robotic system was successfully deployed at the Younggwang Nuclear Unit 1 for the visual inspection of reactor internals.

• 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.

• 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.

• 동력기계공학회지
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• 제6권1호
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• pp.96-101
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• 2002

In this paper, we address the problem of controlling an end-effector to track and grab a moving target using the visual servoing technique. A visual servo mechanism based on the image-based servoing principle, is proposed by using visual feedback to control an end-effector without calibrated robot and camera models. Firstly, we consider the control problem as a nonlinear least squares optimization and update the joint angles through the Taylor Series Expansion. And to track a moving target in real time, the Jacobian estimation scheme(Dynamic Broyden's Method) is used to estimate the combined robot and image Jacobian. Using this algorithm, we can drive the objective function value to a neighborhood of zero. To show the effectiveness of the proposed algorithm, simulation results for a six degree of freedom robot are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3791-3805
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• 2016

The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.3077-3079
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• 1999

A visual servoing method has been proposed based on disturbance observer to eliminate the effect of the off-diagonal component of image feature Jacobian, since performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability could be improved when an image feature Jacobian was given as a block diagonal matrix. In this paper, experimental results of disturbance observer-based visual servoing are discussed where Samsung FARAMAN-ASl 6-axis industrial robot manipulator is employed. Also, the feature saturator is proposed to stabilized the disturbance observer loop by saturating the differential changes of the image features.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.299-301
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• 1994

Visual feedback has traditionally been used in robot manipulator control to a limited extent. However in varying environment, visual data is needed to control the manipulator to complete the desired task. In this paper we present a method of manipulator control scheme called image-based visual servo. In this scheme we use image data as feedback to control robot manipulator. And we also show the experimental results with an industrial robot manipulator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1269-1271
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• 1996

This paper presents a visual servoing combined by evolutionary algorithms and neural network for a robotic manipulators to control position and orientation of the end-effector. Using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we generate the control input to agree the target image, to realize the visual servoing. The validity and effectiveness of the proposed control scheme will be verified by computer simulations.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.88-92
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• 2011

This paper looks at the development of the visual system of robots, and the development of image processing algorism to measure the size of an object and the distance from robot to an object for the visual system. Robots usually get the visual systems with a camera for measuring the size of an object and the distance to an object. The visual systems are accurately impossible the size and distance in case of that the locations of the systems is changed and the objects are not on the ground. Thus, in this paper, we developed robot's visual system to measure the size of an object and the distance to an object using two cameras and two-degree robot mechanism. And, we developed the image processing algorism to measure the size of an object and the distance from robot to an object for the visual system, and finally, carried out the characteristics test of the developed visual system. As a result, it is thought that the developed system could accurately measure the size of an object and the distance to an object.