Concurrent mapping and localization applied to SNUUV I

Abstract

This paper describes concurrent mapping and localization (CML) algorithm suitable for localizing the SNUUV I, a small test autonomous underwater vehicle (AUV) developed by Seoul National University. Increasing use of AUV has led to the development of nontraditional navigation method such as CML. CML is intended to provide relative position by extracting information from the environment that AUV passes through. A technique for CML algorithm which uses several range sonars is presented. This technique utilizes an extended Kalman filter (EKF) to estimate the location of the AUV. In order for the algorithm to work, the stored targets must be associated to the sonar returns at each time step. Given the nature of sonar data, false returns will complicate the process. The Nearest Neighbor Standard Filter (NNSF) is used to choose the target. The proposed CML algorithm has been tested by simulation performed under various conditions, and the experiment conducted in the towing tank and the results of test are presented