• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.590-593
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• 2001

In this paper we describe the 6-axes robot's position determination using a stereo vision and an image based control method. When use a stereo vision, it need a additional time to compare with mono vision system. So to reduce the time required, we use the stereo vision not image Jacobian matrix estimation but depth estimation. Image based control is not needed the high-precision of camera calibration by using a image Jacobian. The experiment is executed as devide by two part. The first is depth estimation by stereo vision and the second is robot manipulator's positioning.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.2
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• pp.63-67
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• 2011

This paper presents the mobile robot control based on vision system. The proposed vision based controller consist of the camera tracking controller and the formation controller. Th e camera controller has the adaptive gain based on IBVS. The formation controller which is designed in the sense of the Lyapunov stability follows the leader. Simluation results show that the proposed vision based mobile robot control is validated for indoor mobile robot applications.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2447-2449
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• 2003

In this paper, optimal fuzzy systems using vector quantization and fuzzy logic controllers are designed for vision-based robot control systems. The complexity of the optimal fuzzy system for vision-based control systems is so great that it can not be applied to real vision-based control systems or it can not be useful, because there are so many input-output pairs. Therefore, we generally use the clustering of input-output pairs, in order to reduce the complexity of optimal fuzzy systems. To increase the effectiveness of the clustering, a vector quantization clustering method is proposed. In order to verify the effectiveness of the proposed method experimentally, it is applied to a vision-based arm robot control system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.605-607
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• 1997

According to the way of the robot control, the robot systems of all the teams which participate in the MIROSOT can be divided into three categories : the remote brainless system, the vision-based system and the robot-based system. The MIRAGE I robot control system uses the last one, the robot-based system. In the robot-based system the host computer with the vision system transmits the data on only the location of the ball and the robots. Based on this robot control method, we took part in the MIROSOT '96 and the MIROSOT '97.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.180.4-180
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• 2001

This paper describes a vision-based line-tracking system for AGV and steering control scheme. For detect the guideline quickly and exactly, We use four line-points which complement and predict each other. This low-cost line-tracking system is efficiently using PC-based real-time vision processing, Steering control is studied through an steering controller with guide-line angle and line-point error. This method is tested via a typical AGV with a single camera in laboratory environment.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1089-1099
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• 2015

This paper proposes vision-based collision risk estimation method for an unmanned surface vehicle. A robust image-processing algorithm is suggested to detect target obstacles from the vision sensor. Vision-based Target Motion Analysis (TMA) was performed to transform visual information to target motion information. In vision-based TMA, a camera model and optical flow are adopted. Collision risk was calculated by using a fuzzy estimator that uses target motion information and vision information as input variables. To validate the suggested collision risk estimation method, an unmanned surface vehicle experiment was performed.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.95-101
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• 2013

The paper investigates the geometric effect of landmarks to the navigation error in the landmark based 3D vision navigation and introduces the INS/Vision integrated navigation system considering its effect. The integrated system uses the vision navigation results taking into account the dilution of precision for landmark geometry. Also, the integrated system helps the vision navigation to consider it. An indirect filter with feedback structure is designed, in which the position and the attitude errors are measurements of the filter. Performance of the integrated system is evaluated through the computer simulations. Simulation results show that the proposed algorithm works well and that better performance can be expected when the error characteristics of vision navigation are considered.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.23-31
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• 2002

We proposed a concept of a desktop micro device factory for visually servoed teleoperated microassembly assisted by a virtual reality (VR) interface. It is composed of two micromanipulators equipped with micro tools operating under a light microscope. First a manipulator, control method for the micro object to follow a planned trajectory in pushing operation is proposed undo. vision based-position control. Then, we present the cooperation control strategy of the micro handling operation under vision-based force control integrating a sensor fusion framework approach. A guiding-system based on virtual micro-world exactly reconstructed from the CAD-CAM databases of the real environment being considered is presented for the imprecisely calibrated micro world. Finally, some experimental results of microassembly tasks performed on millimeter-sized components are provided.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.279-279
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• 2000

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts fur the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell fur automatic test and assembling in S company.