• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.454-459
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• 2006

The research and development for autonomous mobile robots has widely been reported. This paper describes a fuzzy logic based visual servoing system for an autonomous mobile robot. An existing system always needs to keep a moving object in overall image. This makes difficult to move the autonomous mobile robot spontaneously. In this paper we first explain an autonomous mobile robot and fuzzy logic system. And then we design a fuzzy logic based visual servoing system. We extract some features of the object from an overall image and then design a fuzzy logic system for controlling the visual servoing system to an exact position. We here introduce a shooting robot that can track an object and hit it. We show that the proposed system presents a desirable performance by a computer simulation and some experiments.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.15-24
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• 1996

This paper presents a new method for visual servoing to control the pose(position and orientation) of the robotic manipulators for grasping the 3-D moving object whose initial pose and moving informations are unknown by using the stereo camera. The stereo camera is mounted on the end-effector of robotic manipulator. In order to track the current pose of robotic manipulator to the desired pose, we use the image Jacobian, which is described by the differential transform, relating the change in image feature point to the change in the object's pose with respect to the camera. In this paper the simple PD controller is adopted for the robotic manipulator to track the desired pose. Finally, the effectiveness of the proposed method is confirmed by some computer simulations.

• 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 the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.595-601
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• 2011

This paper presents balancing control of inverted pendulum on the ROBOKER arm using visual information. The angle of the inverted pendulum placed on the robot arm is detected by a stereo camera and the detected angle is used as a feedback and tracking error for the controller. Thus, the overall closed loop forms a visual servoing control task. To improve control performance, neural network is introduced to compensate for uncertainties. The learning algorithm of radial basis function(RBF) network is performed by the digital signal controller which is designed to calculate floating format data and embedded on a field programmable gate array(FPGA) chip. Experimental studies are conducted to confirm the performance of the overall system implementation.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.403-410
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• 2016

This paper proposes a robust image-based visual servoing scheme using a nonlinear observer for a monocular eye-in-hand manipulator. The proposed control method is divided into a range estimation phase and a target-tracking phase. In the range estimation phase, the range from the camera to the target is estimated under the non-moving target condition to solve the uncertainty of an interaction matrix. Then, in the target-tracking phase, the feature point uncertainty caused by the unknown motion of the target is estimated and feature point errors converge sufficiently near to zero through compensation for the feature point uncertainty.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.781-787
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• 2015

This paper proposes a hybrid visual servoing algorithm for the object tracking by a mobile robot with the stereo camera. The mobile robot with the stereo camera performs an object recognition and object tracking using the SIFT and CAMSHIFT algorithms for the hybrid visual servoing. The CAMSHIFT algorithm using stereo camera images has been used to obtain the three-dimensional position and orientation of the mobile robot. With the hybrid visual servoing, a stable balance control has been realized by a control system which calculates a desired angle of the center of gravity whose location depends on variations of link rotation angles of the manipulator. A PID controller algorithm has adopted in this research for the control of the manipulator since the algorithm is simple to design and it does not require unnecessary complex dynamics. To demonstrate the control performance of the hybrid visual servoing, real experiments are performed using the mobile manipulator system developed for this research.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.989-994
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• 2011

This study aims to demonstrate the feasibility of a visual servoing-based paired structured light (SL) robot for estimating structural displacement under various external loads. The former paired SL robot, which was proposed in the previous study, was composed of two screens facing with each other, each with one or two lasers and a camera. It was found that the paired SL robot could estimate the translational and rotational displacement each in 3-DOF with high accuracy and low cost. However, the measurable range is fairly limited due to the limited screen size. In this paper, therefore, a visual servoing-based 2-DOF manipulator which controls the pose of lasers is introduced. By controlling the positions of the projected laser points to be on the screen, the proposed robot can estimate the displacement regardless of the screen size. We performed various simulations and experimental tests to verify the performance of the newly proposed robot. The results show that the proposed system overcomes the range limitation of the former system and it can be utilized to accurately estimate the structural displacement.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.65-73
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• 1997

This paper proposes a new method of the structure pruning of dynamic recurrent neural networks (DRNN) using evolutionary computations. In general, evolutionary computations are population-based search methods, therefore it is very useful when several different properties of neural networks need to be optimized. In order to prune the structure of the DRNN in this paper, we used the evolutionary programming that searches the structure and weight of the DRNN and evolution strategies which train the weight of neuron and pruned the net structure. An addition or elimination of the hidden-layer's node of the DRNN is decided by mutation probability. Its strategy is as follows, the node which has mhnimum sum of input weights is eliminated and a node is added by predesignated probability function. In this case, the weight is connected to the other nodes according to the probability in all cases which can in- 11:ract to the other nodes. The proposed pruning scheme is exemplified on the stabilization and position control of the inverted-pendulum system and visual servoing of a robot manipulator and the effc: ctiveness of the proposed method is demonstrated by numerical simulations.

• Journal of Ocean Engineering and Technology
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• v.21 no.3 s.76
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• pp.33-39
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• 2007

The more deeply the researches make progress in ocean researches including the seabed resource investigation or the oceanic ecosystem investigation, the more important the role of UUV gets. In case of study on the deep sea, there are difficulties in telecommunications between AUV and ships, and in data communication and recharging. Therefore, docking is required. In AUV docking system, the AUV should identify the position of docking device and make contact with a certain point of docking device. MOERI (Maritime & Ocean Engineering Research Institute), KORDI has conducted the docking testing on AUV ISIMI in KORDI ocean engineering water tank. As AUV ISIMI approachs the docking device, there is some cases of showing an unstable attitude, because the lights which is on Image Frame are disappeared. So we propose the docking algorithm that is fixing the rudder and stem, if the lights on image frame are reaching the specific area in the Image Frame. Also we propose the new docking device, which has a variety of position and light number. In this paper, we intend to solve the some cases of showing an unstable attitude that were found in the testing, which, first, will be identified the validity via simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.375-381
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• 2005

Usually genetic algorithms are used to design optimal system. However the performance of the algorithm is determined by the fitness function and the system environment. It is expected that a co-evolutionary algorithm, two populations are constantly interact and co-evolve, is one of the solution to overcome these problems. In this paper we propose three types of co-evolutionary algorithm to solve GA-Hard problem. The first model is a competitive co-evolutionary algorithm that solution and environment are competitively co-evolve. This model can prevent the solution from falling in local optima because the environment are also evolve according to the evolution of the solution. The second algorithm is schema co-evolutionary algorithm that has host population and parasite (schema) population. Schema population supply good schema to host population in this algorithm. The third is game model-based co-evolutionary algorithm that two populations are co-evolve through game. Each algorithm is applied to visual servoing, robot navigation, and multi-objective optimization problem to verify the effectiveness of the proposed algorithms.