해저 집광차량의 위치 추정을 위한 확장 칼만 필터 알고리즘

• Published in: Han-guk haeyang gonghak hoeji (Online) Vol. 19; no. 2; pp. 82 - 89
• Main Authors: 원문철(MOON-CHEOL WON), 차혁상(HYUK-SANG CHA), 홍섭(SUP HONG)
• Format: Journal Article
• Language: Korean
• Published: 한국해양공학회 2005
• Subjects: 해양공학; Localization of Underwater Mining Vehicle 해저주행차량 위치추정; Tracked Vehicle 궤도차량; EKF(Extended Kalman Filter) 확장 칼만 필터
• ISSN: 1225-0767; 2287-6715

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 dawn 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.