무인 잠수정 3자유도 운동 실험에 대한 무향 칼만 필터 기반 SLAM기법 적용

다국어 초록 (Multilingual Abstract)

The increased use of unmanned underwater vehicles (UUV) has led to the development of alternative navigatianal methods that do not employ acoustic beacans and dead reckoning sensors. This paper describes a simultaneous localizatian 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 location of the UUV and surrounding objects. In order to work efficiently, the nearest neighbor standard filter is introduced as the data association algorithm is 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.

참고문헌 (Reference)

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