• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.126.3-126
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• 2001

A new method to govern the navigation of a mobile robot is proposed based on the following two procedures: one is to achieve vision information by using a 2 D-O-F camera as a communicating medium between a man and a mobile robot and the other is to analyze and to behave according to the recognized hand gesture commands. In the previous researches, mobile robots are passively to move through landmarks, beacons, etc. To incorporate various changes of situation, a new control system manages the dynamical navigation of a mobile robot. Moreover, without any generally used expensive equipments or complex algorithms for hand gesture recognition, a reliable hand gesture recognition system is efficiently implemented to convey the human commands to the mobile robot with a few constraints.

• 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.

• 한국해양공학회지
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• 제29권5호
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• pp.392-397
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• 2015

An autonomous underwater vehicle (AUV) can perform flexible operations even in complex underwater environments because of its autonomy. Localization is one of the key components of this autonomous navigation. Because the inertial navigation system of an AUV suffers from drift, observing fixed objects in an inertial reference system can enhance the localization performance. In this paper, we propose a method of AUV localization using visual measurements of underwater structures. A camera measurement model that emulates the camera’s observations of underwater structures is designed in a particle filtering framework. Then, the particle weight is updated based on the extracted visual information of the underwater structures. The proposed method is validated based on the results of experiments performed in a structured basin environment.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.105-110
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• 2009

In this paper, we proposed a navigation algorithm of the mobile robot for obstacle avoidance using a circular path planning method. The proposed method makes circular paths in order to avoid obstacles in the front side of the mobile robot. An optimal path for approaching to the target is selected and the linear and angular speeds for stable moving of the mobile robot are controlled. Obstacles are detected by image processing which reduce image data obtained from a web camera. Performance of the proposed algorithm is shown by experiments with application to the Pioneer-2DX mobile robot.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2393-2395
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• 2001

The mobile robot is used as an instrument of transportation in automated plant. But the greater part of the moving method is the wheel-type. The wheel-type robot is easier control than the track-type, However the track-type is better than the wheel-type in bad landform(bend landform, an incline plane, stairs). In this paper, we propose the navigation algorithm of track-type robot in order to improve a defect of wheel-type. We experiment in bend landfrom and even ground to differentiate the navigation method. To estimate robot pose, we use the 80196 in a close distance and the vision-board in a long distance. Each data is managed in main PC and then the part of managing correspond to every sensor. We also use twelve supersonic wave-sensors to recognize external surroundings. As the result of experiment, we analyze the algorithm of control and make possible surroundings-adaptation.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1999년도 추계학술대회논문집
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• pp.309-314
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• 1999

The major movement block of the containers is range between apron and designation points on yard in container terminal. The yard tractor operated by human takes charge of it's movement in conventional container terminal. In unmanned container terminal, UCT(unmanned container transporter) has charge of the yard tractor's role and the navigation path is ordered from upper level control system. The unmanned container terminal facilities must have docking system that guided landing line to have high speed travelling and precision positioning in unmanned container terminal. The general method for docking uses the vision system with CCD camera, infra red, and laser. This paper describes the investigation for the developed docking method in view point of merit and demerit and introduces 속 result of developing the docking system with LSB(laser slit beam).

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.36.4-36
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• 2001

A robust and reliable path recognition system is one necessary component for the autonomous navigation of a mobile robot to help determining its current position in its navigation map. This paper describes a computer visual path-recognition system using on-board video camera as vision-based driving assistance for an autonomous navigation mobile robot. The common problem for a visual system is that its reliability was often influenced by different lighting conditions. Here, two different image processing methods for the path detection were developed to reduce the effect of the luminance: one is based on the RGB color model and features of the path, another is based on the HSV color model in the absence of luminance.

• 제어로봇시스템학회논문지
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• 제19권11호
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• pp.1029-1035
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• 2013

This paper proposes a real time lane detection algorithm using LRF (Laser Range Finder) for autonomous navigation of a mobile robot. There are many technologies for safety of the vehicles such as airbags, ABS, EPS etc. The real time lane detection is a fundamental requirement for an automobile system that utilizes outside information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. By the vision-based system, recognition of environment for three dimensional space becomes excellent only in good conditions for capturing images. However there are so many unexpected barriers such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement. In this paper, we introduce a three dimensional lane detection algorithm using LRF, which is very robust against the illumination. For the three dimensional lane detections, the laser reflection difference between the asphalt and lane according to the color and distance has been utilized with the extraction of feature points. Also a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been verified through the real experiments.

• 한국지능시스템학회논문지
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• 제17권7호
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• pp.901-906
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• 2007

미지의 환경에서 이동로봇이 자율 주행을 할 수 있기 위해서는 경로 설정 및 장애물 회피가 필수적인 요소이다. 이를 위해 본 논문에서는 비전과 IR 센서로부터 획득한 데이터와 퍼지규칙을 이용하는 자율 주행 알고리즘을 구현하고자 한다. 로봇과 장애물과의 거리가 멀리 떨어져 있는 경우는 비전에서 얻은 2차원 이미지를 메디안 필터링, 에지 추출, 모폴로지, 세선화 과정을 거쳐 임시 목표물을 설정한 다음, 거리 변화율 기법과 퍼지 규칙을 이용하여 경로 설정을 한다. 로봇과 장애물과의 거리가 근접할 경우는 IR 센서를 이용하여 경로 설정 및 근접 장애물 회피를 하도록 한다. 그리고 본 논문에서는 제안된 퍼지규칙을 이용한 데이터 융합 알고리즘이 이동로봇을 미지의 환경에서 보다 효율적으로 주행하게 할 수 있음을 실제 실험을 통해 보여주고자 한다.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.