Autonomous Underwater Vehicles: A New Accurate Navigation Strategy

Currently, many important scientific and industrial activities in the underwater environment are based on Autonomous Underwater Vehicles (AUVs). The complexity and the accuracy required by these tasks highlight the need for accurate, reliable and robust navigation strategies. A key aspect for such missions is the availability of an accurate algorithm able to estimate in real-time the vehicle position. These algorithms usually exploits simple and fast kinematic vehicle models and linear estimators. However, the underwater environment really complicates the estimation process: for example, the Global Positioning System (GPS) is not exploitable underwater. Consequently, the real-time vehicle position estimation becomes very hard and the classical estimation algorithms are often unreliable. In this work, an innovative navigation strategy based on the Unscented Kalman Filter (UKF) and especially designed for AUVs is presented by the authors. The new algorithm turns out to be quite effective if applied to this class of vehicles, providing accurate results (compared to standard navigation algorithms) and maintaining the computational load affordable for mobile robots hardware. The proposed strategy has been experimentally validated using the navigation data acquired during sea tests performed by the two Typhoon AUVs, developed and built by the Department of Industrial Engineering (DIEF) of the University of Florence in the framework of the THESAURUS Tuscany Region project for exploration and surveillance of underwater archaeological sites and of the FP7 European ARROWS project, during a 14 months timespan. The experimental data presented in the paper come from three different experimentations at sea, at increasing complexity: the THESAURUS project final sea trial, Livorno, Italy; the CommsNet13 experiment, organized and led by NATO STO CMRE, La Spezia, Italy, and the Breaking the Surface initiative, organized by LABUST, Zagreb University, and held in Biograd Na Moru, Croatia. In particular, the tests executed in the final campaign were performed to preliminary test the cooperative navigation strategy between the two vehicles. The new algorithm has been initially tested offline, providing accurate estimations of the dynamic behaviour of the AUVs.