• 제어로봇시스템학회논문지
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• 제3권5호
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• pp.497-502
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• 1997

In this study an automatic rolling-coil labeling system using robot vision system and peripheral mechanism is proposed and implemented, which instead of the manual labor to attach labels Rolling-coils in a steel mill. The binary image process for the image processing is performed with the threshold, and the contour line is converted to the binary gradient which detects the discontinuous variation of brightness of rolling-coils. The moments invariant algorithm proposed by Hu is used to make it easy to recognize even when the position of the center are different from the trained data. The position error compensation algorithm of six degrees of freedom industrial robot manipulator is also developed and the data of the position of the center rolling-coils, which is obtained by floor mount camera, are transferred by asynchronous communication method. Therefore, even if the position of center is changed, robot moves to the position of center and performs the labeling work successfully. Therefore, this system can be improved the safety and efficiency.

• 제어로봇시스템학회논문지
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• 제15권12호
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• pp.1223-1231
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• 2009

We derive a systematic and iterative calibration algorithm, and position and pose estimation algorithm for the mobile robots in formation system based on the vision system. In addition, we develop a coordinate matching algorithm which calculates matched sequence of order in both extracted image coordinates and object coordinates for non interactive calibration and pose estimation. Based on the results of calibration, we also develop a camera simulator to confirm the results of calibration and compare the results of simulations with those of experiments in position and pose estimation.

• 한국멀티미디어학회논문지
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• 제17권7호
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• pp.787-796
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• 2014

Many mobile robot navigation methods utilize laser scanners, ultrasonic sensors, vision camera, and so on for detecting obstacles and path following. However, human utilizes only vision(e.g. eye) information for navigation. In this paper, we study a mobile robot control method based on only the camera vision. The Gaussian Mixture Model and a shadow removal technology are used to divide the foreground and the background from the camera image. The mobile robot uses a combined CAMSHIFT and KLT feature tracker algorithms based on the information of the foreground to follow a person. The algorithm is verified by experiments where a person is tracked and followed by a robot in a hallway.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.915-919
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• 2003

This paper presents a fuzzy-motion-control based tracking algorithm of mobile robots, which uses the geometrical information derived from the active stereo-vision system mounted on the mobile robot. The active stereo-vision system consists of two color cameras that rotates in two angular dimensions. With the stereo-vision system, the center position and depth information of the target object can be calculated. The proposed fuzzy motion controller is used to calculate the tracking velocity and angular position of the mobile robot, which makes the mobile robot keep following the object with a constant distance and orientation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2019-2023
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• 2005

In this paper, an autonomous omni directional cleaning robot which recognizes an obstacle and a battery charger is introduced. It utilizes a robot vision, ultra sonic sensors, and infrared sensors information along with appropriate algorithm. Three omni-directional wheels make the robot move any direction, enabling a faster maneuvering than a simple track typed robot. The robot system transfers command and image data through Blue-tooth wireless modules to be operated in a remote place. The robot vision associated with sensor data makes the robot proceed in an autonomous behavior. An autonomous battery charger searching is implemented by using a map-building which results in overcoming the error due to the slip on the wheels, and camera and sensor information.

• 제어로봇시스템학회논문지
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• 제2권3호
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• pp.200-208
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• 1996

This paper describes the mechanism, guidance, sensor system, and navigation algorithm of METRO, a free ranging mobile robot. METRO is designed for use in structured surroundings or factory environments rather than unstructured natural environments. An overview of the physical configuration of the mobile robot is presented as well as a description of its sensor system, an omnidirectional laser range finder. Except for the global path planning algorithm, a guidance and a navigation algorithm with a local path planning algorithm are used to navigate the mobile robot. In METRO the computer support is divided into a supervisor with image processing and local path planning and a slave with motor control. The free ranging mobile robot is self-controlled and all processing being performed on board.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1828-1831
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• 1997

this paper, to represent the robot motion approximately in space, delas with algorithm for position recognition of space robot, target and obstacle with vision system in 2-D. And also there are algorithms for precise distance-measuring and calibration usign laser displacement system, and for trajectory selection for optimizing moving to object, and for robot locomtion with air-thrust valve. And the software synthesizing of these algorithms hleps operator to realize the situation certainly and perform the job without any difficulty.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.483-488
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• 2008

An active omni-directional raging system using an omni-directional vision with structured light has many advantages compared to the conventional ranging systems: robustness against external illumination noise because of the laser structured light and computational efficiency because of one shot image containing $360^{\circ}$ environment information from the omni-directional vision. The omni-directional range data represents a local distance map at a certain position in the workspace. In this paper, we propose a matching algorithm for the local distance map with the given global map database, thereby to localize a mobile robot in the global workspace. Since the global map database consists of line segments representing edges of environment object in general, the matching algorithm is based on relative position and orientation of line segments in the local map and the global map. The effectiveness of the proposed omni-directional ranging system and the matching are verified through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.83-86
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• 1987

A vision algorithm is presented for the separation of near objects from distant objects. In the algorithm, a difference field of a stereo pair of images is computed to obtain the range information and the median filter is used for the suppression of distant objects. The objects within a given distance is segmented by thresholding the gray scale cross-section of the median filtered difference field. The experiment is performed in a laboratory setting.

• 제어로봇시스템학회논문지
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• 제14권2호
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• pp.168-177
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• 2008

Path finding is a key element in the navigation of a mobile robot. To find a path, robot should know their position exactly, since the position error exposes a robot to many dangerous conditions. It could make a robot move to a wrong direction so that it may have damage by collision by the surrounding obstacles. We propose a method obtaining an accurate robot position. The localization of a mobile robot in its working environment performs by using a vision system and Virtual Reality Modeling Language(VRML). The robot identifies landmarks located in the environment. An image processing and neural network pattern matching techniques have been applied to find location of the robot. After the self-positioning procedure, the 2-D scene of the vision is overlaid onto a VRML scene. This paper describes how to realize the self-positioning, and shows the overlay between the 2-D and VRML scenes. The suggested method defines a robot's path successfully. An experiment using the suggested algorithm apply to a mobile robot has been performed and the result shows a good path tracking.