• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1778-1779
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• 2011

The location of outdoor mobile robot is obtained using global coordinates from GPS. However, the error generated by GPS is about 10m ~ 100m, so the precise control is difficult. D-GPS has the error value of 1m and it is very accurate, but the price is very expensive. In this paper, a method to reduce the error in global coordinates is proposed using two low-cost GPS for the autonomous navigation control of outdoor mobile robot.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1459-1466
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• 2018

Robots which detect human and recognize action are important factors for human interaction, and many researches have been conducted. Recently, deep learning technology has developed and learning based robot's technology is a major research area. These studies require a database to learn and evaluate for intelligent human perception. In this paper, we propose a multi-modal sensor-based image database condition considering the security task by analyzing the image database to detect the person in the outdoor environment and to recognize the behavior during the running of the robot.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.800-808
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• 2008

This paper presents a localization algorithm of the outdoor wheeled mobile robot using the sensor fusion method based on indirect Kalman filter(IKF). The wheeled mobile robot considered with in this paper is approximated to the two wheeled mobile robot. The mobile robot has the IMU and encoder sensor for inertia positioning system and GPS. Because the IMU and encoder sensor have bias errors, divergence of the estimated position from the measured data can occur when the mobile robot moves for a long time. Because of many natural and artificial conditions (i.e. atmosphere or GPS body itself), GPS has the maximum error about $10{\sim}20m$ when the mobile robot moves for a short time. Thus, the fusion algorithm of IMU, encoder sensor and GPS is needed. For the sensor fusion algorithm, we use IKF that estimates the errors of the position of the mobile robot. IKF proposed in this paper can be used other autonomous agents (i.e. UAV, UGV) because IKF in this paper use the position errors of the mobile robot. We can show the stability of the proposed sensor fusion method, using the fact that the covariance of error state of the IKF is bounded. To evaluate the performance of proposed algorithm, simulation and experimental results of IKF for the position(x-axis position, y-axis position, and yaw angle) of the outdoor wheeled mobile robot are presented.

• 제어로봇시스템학회논문지
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• 제13권2호
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• pp.86-92
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• 2007

This paper presents the development of fire-fighting and rescue robot for Outdoor Environment. In the procedure of this development, we follow Target Oriented Design (TOD) which is recognized as the systematic methodology to design a system by specifying the target clearly. For some real fire fighting tasks (e.g. tasks in shopping street and a market), narrow road make it difficult for existing fire engine to access the firing place. On the other hand, for dangerous tasks (e.g. gasoline station and a storehouse) the explosive materials make it impossible for fire-fighters to access the firing place. Moreover, the smoke and the high-temperature caused by fire make fire fighting difficult. In this situation, the solution is to develop the fire-fighting and rescue robot. TOD is performed firstly by analyzing the environment properties of fro place and the demanded tasks and the fire-fighting and rescue robot is manufactured. For safety, the fire fighting robot should be controlled by remote operation to keep the operator away from the fire, and the control system is divided into three parts: the robot controllers, controller for remote operating device and wireless communication system. We have selected and developed appropriate hardware and software for each part of control system with considering TOD. As a result, the fire-fighting robot functions correctly and the performance and usefulness of our control architecture is validated by successfully performing some fire-fighting tasks.

• 제어로봇시스템학회논문지
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• 제20권12호
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• pp.1284-1289
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• 2014

In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2017년도 춘계공동학술대회
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• pp.174-174
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• 2017

농지의 구성물을 인식하는 기술은 농작업 기계를 로봇으로 전환하는데 필요한 기술 중 하나이다. 하지만 실외에서는 태양광과 날씨 변화에 따른 광 조건의 변화가 매우 커서 기존의 영상처리 방법으로 구성물을 인지하는데 한계가 있었다. 본 연구에서는 광 조건의 변화에 따른 영향을 줄이는 방안으로 IR 이미지를 이용한 농지 구성물의 인지를 수행하였다. 농지 구성물로는 토양, 식물, 멀칭비닐, 자갈을 선정하였다. 농지의 IR 이미지에서 농지 구성물을 구별하기 위한 픽셀값을 작게 적용하면 미세한 구분은 가능하지만 토양, 식물, 멀칭 비닐 등을 구성물 단위로 구별할 대는 후처리가 필요로 해지는 문제가 발생하였다. 본 연구에서는 IR 영상의 픽셀값을 평균 처리하여 농지 구성물의 인지를 수행 때의 효과를 확인 하였다. 평균 처리하는 픽셀값이 많을수록 처리속도가 빠르고, 작은 노이즈를 제어하는 효과가 있었지만, 픽셀값이 너무 커지면 구조물의 구별 정확도가 떨어졌다. 이 결과를 바탕으로 농지 구성물 인지를 위한 효율적인 IR 이미지 평균 처리 수준을 확인하였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2005년도 가을 학술발표논문집 Vol.32 No.2 (2)
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• pp.616-618
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• 2005

본 논문은 적외선 리모트 컨트롤러로 제어가 가능한 가정용 소형 로봇인 $Robosapien^{TM}$을 홈 네트워크 제어를 위한 홈 서버를 통해 직접 제어할 수 있는 제어 소프트웨어를 개발하였다. 또한 $Robosapien^{TM}$의 연속적인 동작을 쉽게 프로그래밍하고 실행시킬 수 인터프리터 (interpreter)의 세부 구현내용을 기술하였다. 본 구현은 컴퓨터 프로그래밍의 개념 정립이 부족한 일반 사용자나 컴퓨터 프로그밍에 관심이 많은 학생들이 쉽게 프로그래밍 할 수 있는 비주얼 프로그래밍 도구를 개발하였다. 특히 구현 시 필요한 구성 요소 및 기능을 설계하고 사용자의 편의성을 고려한 편리한 GUI(Graphical User Interface)의 구현에 중점을 두었다. 본 비주얼 프로그래밍 도구는 가정의 데스크톱 PC뿐만 아니라, 실외에서 PDA와 같은 소형 이동단말기를 이용하여 원격으로 가정의 홈 서버에 접속하여 $Robosapien^{TM}$의 동작을 실시간으로 제어할 수 있으며 가정의 웹 카메라를 통하여 $Robosapien^{TM}$이 정확하게 동작하고 있는지를 원격으로 확인할 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2365-2368
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• 2001

This paper describes a fuzzy steering controller for an autonomous mobile robot with MR sensor. Using the magnetic field($B_{x}$, $B_{y}$, $B_{z}$) obtained from the MR sensor, we designed fuzzy controller for driving on the road center. Fuzzy rule base was built to magnetic field($B_{x}$, $B_{y}$, $B_{z}$). To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, dynamic model of mobile robot and coordinate transformation. A computer simulation of the robot (including mobile robot dynamics and steering) was used to verify the steering performance of the mobile robot controller using the fuzzy logic. Good results were obtained by computer simulation. So, we confirmed the robustness of the proposed fuzzy controller by computer simulation. Also, we know that proposed control algorithm was applied to real autonomous mobile robot.

• 센서학회지
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• 제19권3호
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• pp.246-257
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• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• 해양환경안전학회지
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• 제29권7호
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• pp.980-991
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• 2023

항만 내 선박과 부두의 사고를 예방하기 위하여 통항 및 접안 안전성 평가를 통하여 안전한 부두가 건설되어 관리하고 있으나, 선박의 접안 및 계류 과정에서 선박이 부두에 충돌하거나 로프로 인한 인명사고의 발생 등 예측할 수 없는 사고들이 종종 발생한다. 자동계류장치는 선박의 신속하고 안전한 계류를 위한 자동화된 시스템으로 로봇 매니퓰레이터와 흡착 패드로 구성된 탈/부착 메커니즘을 가지고 있다. 본 논문은 자동계류장치의 흡착 패드의 위치 및 속도제어에 필요한 선체와의 변위 및 속도 측정 시스템을 다룬다. 자동계류장치에 적합한 측정 시스템을 설계하기 위하여, 본 논문은 우선 센서의 성능 및 실외 환경적 특성 분석을 수행한다. 다음으로 이러한 분석 결과를 토대로 실외 부두환경에서 설치되는 자동계류장치에 적합한 변위 및 속도 측정시스템의 구성 및 설계 방법에 대해 기술한다. 또한 센서의 측정상태 감지 및 속도 추정을 위한 알고리즘을 제시한다. 제안된 방법은 다양한 속도 구간에서의 변위 및 속도 측정 실험을 통해 그 유용성을 검증한다.