Vision-based localization and mapping system for AUV intervention

This paper presents a modular localization and mapping system for intervention autonomous underwater vehicles working in semi-structured environments with known landmarks. The system is divided in several modules to make it as generic as possible. Two visual detection algorithms can be used to compute the position of known landmarks by comparing the images taken by the vehicle against an a priori known template. Navigation data, provided by standard navigation sensors, is adapted and merged together with landmark positions by means of an extended Kalman filter. This filter is capable of estimating vehicle position and linear velocity as well as the position of detected landmarks in real-time. Experiments performed with the Girona 500 AUV in a water tank demonstrate the proposed method.