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해저 집광차량의 위치 추정을 위한 확장 칼만 필터 알고리즘
원문철(MOON-CHEOL WON),차혁상(HYUK-SANG CHA),홍섭(SUP HONG) 한국해양공학회 2005 韓國海洋工學會誌 Vol.19 No.2
This study deals with the development of the extended Kalman filter(EKF) algorithm for the localization of underwater mining vehicles. Both simulation and experimental studies in a test bed are carried out. For the experiments, a scale down tracked vehicle is run in a soil bin containing cohesive soil of bentonite-water mixture. To develop the EKF algorithm, we use a kinematic model including the inner/outer track slips and the slip angle for the vehicle. The measurements include the inner and outer wheel speeds from encoders, the heading angle from a compass sensor and a fiber optic rate gyro, and x and y coordinate position values from a vision system. The vision sensor replaces the LBL(Long Base Line) sonar system used in the real underwater positioning situations. Artificial noise signals mimicking the real LBL noise signal are added to the vision sensor information. To know the mean slip values of the tracks in both straight and cornering maneuver, several trial running experiments are executed before applying the EKF algorithm. Experimental results show the effectiveness of the EKF algorithm in rejecting the sensor measurements noise. Also, the simulation and experimental results show close correlations.
원문철(MOON-CHEOL WON),홍성국(SEONG-KUK HONG),정윤하(YUN-HA JUNG),김선영(SUN-YOUNG KIM),손남선(NAM-SUN SON),윤현규(HYUN-GYU YOON) 한국해양공학회 2008 韓國海洋工學會誌 Vol.22 No.3
his study discusses the design of an automatic berthing control algorithm for ships with a bow thruster and a stern thruster, as well as a rudder. A nonlinear mathematical model for the law speed maneuvering of ships was used to design a MlMO (multi-input multi-output) nonlinear control algorithm. The algorithm consists of two parts, the forward velocity control and heading angle control. The control algorithm was designed based on the longitudinal and yaw dynamic models of ships. The desired heading angle was obtained by the so-called "Line of Sight" method. An optimal control force allocation method for the rudder and the thrusters is suggested. The nonlinear control algorithm was tested by numerical simulations using MATLAB, and showedgood tracking performance.
이상진(Sang-Jin Lee),원문철(Moon-Cheol Won) 대한기계학회 2011 대한기계학회 춘추학술대회 Vol.2011 No.10
Many mobile robot navigation methods utilize laser scanners, ultrasonic sensors, vision camera, and so on for detecting obstacles. 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. The mobile robot use a combined CAMSHIFT and KLT feature tracker Algorithms based on the information of the foreground to track a person.
영상정보만을 이용한 사람과 로봇 간 실시간 상대위치 추정 알고리즘
이정욱(Jung-uk Lee),원문철(Moon-cheol Won) 대한기계학회 2011 대한기계학회 춘추학술대회 Vol.2011 No.10
We propose a real time algorithm of person to robot relative position estimation using a moncular camera. We find the head and shoulder area of a person using HOG(Histogram of Oriented Gradient) feature vector and SVM(Support Vector Machine) classifier. The size and location of the detected area is utilized to calculate the relative distnace and angle between a person and a camera on robot. To increase the speed of the algorithm, we use GPU and CUDA library of NVIDIA and the resulting algorithm speed is about 15Hz. The correctness of the algorithm is campared with output of a SICK laser scanner