• 한국자동차공학회논문집
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• 제11권6호
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• pp.222-228
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• 2003

Lane departure avoidance system is one of the key technologies for the future active-safety passenger cars. The lane departure avoidance system is composed of two subsystems; lane sensing algorithm and active-steering controller. In this paper, the road image is obtained by vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active-steering controller is designed to prevent the lane departure. The developed active-steering controller can be realized by steer-by-wire actuator. The lane-sensing algorithm and active-steering controller are implemented into the steering HILS(Hardware-In-the-Loop Simulation) and their performance is evaluated with a human driver in the loop.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.297-304
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• 1997

In stereo vision, camera modeling is very important because the accuracy of the three dimensional locations depends considerably on it. In the existing stereo camera models, two camera planes are located in the same plane or on the optical axis. These camera models cannot be used in the active vision system where it is necessary to obtain two stereo images simultaneously. In this paper, we propose four kinds of stereo camera models for active stereo vision system where focal lengths of the two cameras are different and each camera is able to rotate independently. A single closed form solution is obtained for all models. The influence of the stereo camera model to the field of view, occlusion, and search area used for matching is shown in this paper. And errors due to inaccurate focal length are analyzed and simulation results are shown. It is expected that the three dimensional locations of objects are determined in real time by applying proposed stereo camera models to the active stereo vision system, such as a mobile robot.

• Journal of Advanced Marine Engineering and Technology
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• 제36권5호
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• pp.674-682
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• 2012

A new intelligent stereo vision sensor system was studied for the motion and depth control of unmanned vehicles. A new bottom-up saliency map model for the human-like active stereo vision system based on biological visual process was developed to select a target object. If the left and right cameras successfully find the same target object, the implemented active vision system with two cameras focuses on a landmark and can detect the depth and the direction information. By using this information, the unmanned vehicle can approach to the target autonomously. A number of tests for the proposed bottom-up saliency map were performed, and their results were presented.

• 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.80-83
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• 2005

A binocular robot vision system having an autonomously moving active viewpoint is proposed. By using this active viewpoint, the system constructs a correspondence between the images of a feature points on the right and left retinas and calculates the spatial coordinates of the feature points. The system incorporates a function of detecting straight lines in an image. To detect lines the system uses Hough transform. The system searches a region surrounded by 4 straight lines. Then the system recognizes the region as a quadrangle. The system constructs a correspondence between the quadrangles in the right and left images. By the use of the result of the constructed correspondence, the system calculates the spatial coordinates of an object. An experiment shows the effect of the line detection using Hough transform, the recognition of the surface of the object and the calculation of the spatial coordinates of the object.

• International Journal of Control, Automation, and Systems
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• 제5권2호
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• pp.184-191
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• 2007

Autonomous navigation of mobile robot requires a ranging system for measurement of distance to environmental objects. It is obvious that the wider and the faster distance measurement gives a mobile robot more freedom in trajectory planning and control. The active omni-directional ranging system proposed in this paper is capable of obtaining the distance for all 3600 directions in real-time because of the omni-directional mirror and the structured light. Distance computation including the sensitivity analysis and the experiments on the omni-directional ranging are presented to verify the effectiveness of the proposed system.

• 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.

• 전기학회논문지
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• 제61권5호
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• pp.735-743
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• 2012

In this paper, we present model predictive control (MPC) applied to lane keeping system (LKS) based on a vision module. Due to a slow sampling rate of the vision system, the conventional LKS using single rate control may result in uncomfortable steering control rate in a high vehicle speed. By applying MPC using multi-rate Kalman filter to active steering control, the proposed MPC-based active steering control system prevents undesirable saturated steering control command. The effectiveness of the MPC is validated by simulations for the LKS equipped with a camera module having a slow sampling rate on the curved lane with the minimum radius of 250[m] at a vehicle speed of 30[m/s].

• 한국공작기계학회논문집
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• 제16권6호
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• pp.110-116
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• 2007

This paper presents a new technique to implement the real-time recognition for shapes and model number of parts based on an active vision approach. The main focus of this paper is to apply a technique of 3D object recognition for non-contacting inspection of the shape and the external form state of precision parts based on the pattern recognition. In the field of computer vision, there have been many kinds of object recognition approaches. And most of these approaches focus on a method of recognition using a given input image (passive vision). It is, however, hard to recognize an object from model objects that have similar aspects each other. Recently, it has been perceived that an active vision is one of hopeful approaches to realize a robust object recognition system. The performance is illustrated by experiment for several parts and models.

• 전자공학회논문지SC
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• 제41권4호
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• pp.39-43
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• 2004

능동적인 비전 시스템의 전형적인 한 테마는 카메라의 시선 고정 문제이다. 여기서 카메라의 시선 고정이란 동적인 물체 상의 지정된 한 점이 항시 이미지의 중앙부에 놓이도록 카메라의 자세를 조정하는 것으로서, 이를 위해서는 카메라에 비친 영상정보를 분석하는 기능과 카메라의 자세를 제어하는 두 가지 기능이 결합되어야 한다. 본 논문에서는 영상분석과 자세제어가 한 개의 프레임 하에서 설계되는 카메라의 시선 고정을 위한 알고리즘을 제안한다. 이 때 제작시의 어려움을 피하고 실시간 응용을 위해서 본 알고리즘은 카메라의 calibration이나 3차원 거리 정보의 복원을 필요로 하지 않도록, 그리고 닫힌 형태(closed-form)가 되도록 설계된다.