Navigation of an Autonomous Underwater Vehicle for Photo Mosaicing of Shallow Vent Areas

Although underwater vent areas are scientifically important, precise photo mosaicing of them is for the following reasons still a hard task. Firstly, the visible range is limited by the turbid water and floating particles. Secondly, the conventional acoustic positioning is vulnerable to the bubble plumes of the vent areas. In this paper a navigation method of an autonomous underwater vehicle (AUV) for photo mosaicing of shallow vent areas where bubbles are spouting is proposed. Simultaneously, this method estimates the position of the AUV and the landmarks, such as bubble plumes and artificial sonar reflectors. The simultaneous localization and mapping (SLAM) based approach enables drift free, accurate, real-time and independent navigation in a local area, which is suitable for photo mosaicing. The proposed method has been implemented on the testbed AUV "Tri-Dog 1" and a tank experiment has been carried out to verify its performance.