DEVELOPMENT OF A UKF-SLAM SCHEME FOR AUTONOMOUS NAVIGATION OF UNMANNED UNDERWATER VEHICLES

Abstract

This paper presents a novel approach to the autonomous navigation of unmanned underwater vehicles (UUVs) using a simultaneous localization and mapping (SLAM) scheme based on an unscented Kalman filter (UKF). The proposed scheme employs a range sonar sensor to collect data and estimate the position of the UUV and surrounding objects in highly nonlinear motion scenarios. The UKF-SLAM scheme was validated through simulations and experiments, including two and three degrees of freedom motion conditions, in a towing tank environment with a real UUV. The results show that the proposed algorithm can accurately estimate the position of the UUV and surrounding objects and perform well under various conditions.