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J. Ocean Eng. Technol. 2009;23(2):58-68.    

Experiments of Unmanned Underwater Vehicle's 3 Degrees of Freedom Motion Applied the SLAM based on the Unscented Kalman Filter
Hwang A-Rom,Seong Woo-Jae,Jun Bong-Huan,Lee Pan-Mook
LIG Nex1,Dept. of Naval and Ocean Engineering Seoul National Univ.,Korea Ocean Research and Development Institute,Korea Ocean Research and Development Institute
무인 잠수정 3자유도 운동 실험에 대한 무향 칼만 필터 기반 SLAM기법 적용
황아롬,성우제,전봉환,이판묵
LIG 넥스원,서울대학교 조선해양공학과,한국해양연구원 해양시스템안전연구소,한국해양연구원 해양시스템안전연구소
Copyright © 2009 The Korean Society of Ocean Engineers     Open access / Under a Creative Commons License
Key Words: Simultaneous localization and mapping (SLAM), Local submap, Unmanned underwater vehicles (UUV), Range sonar, Unscented Kalman filter (UKF), Data association
핵심용어: 무인 잠수정, 거리 측정 소나, 무향 칼만 필터
Abstract
The increased use of unmanned underwater vehicles (UUV) has led to the development of alternative navigational methods that do not employ acoustic beacons and dead reckoning sensors. This paper describes a simultaneous localization and mapping (SLAM) scheme that uses range sonars mounted on a small UUV. A SLAM scheme is an alternative navigation method for measuring the environment through which the vehicle is passing and providing the relative position of the UUV. A technique for a SLAM algorithm that uses several ranging sonars is presented. This technique utilizes an unscented Kalman filter to estimate the locations of the UUV and surrounding objects. In order to work efficiently, the nearest neighbor standard filter is introduced as the data association algorithm in the SLAM for associating the stored targets returned by the sonar at each time step. The proposed SLAM algorithm was tested by experiments under various three degrees of freedom motion conditions. The results of these experiments showed that the proposed SLAM algorithm was capable of estimating the position of the UUV and the surrounding objects and demonstrated that the algorithm will perform well in various environments.
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