Shallow water bathymetry using a DVL-based mapping strategy

Mapping underwater environments is an essential task to be achieved during autonomous missions, which can be helpful in several fields, such as hydrogeology, speleology and geology. Since the water reduces the camera field of view and complicates identifying good reliable image features, acoustic sensors, which can penetrate water for long ranges in almost every scenario, are the most employed for underwater navigation and mapping. The most exploited underwater navigation approaches are based on using a Doppler Velocity Log (DVL) for linear speed vector estimation. The DVL sensor provides, when the bottom-lock is possible, highly precise linear velocity estimates, but it can also be employed to provide a bathymetry of the sea floor. This paper presents a mapping framework that employs DVL readings, and it is specifically tailored to Autonomous Underwater Vehicles (AUVs). The proposed method is tested through the use of data recorded during sea trials performed in 2022 with FeelHippo AUV, a vehicle developed by the Department of Industrial Engineering of the University of Florence (UNIFI DIEF), in La Spezia (Italy), at the Centro di Supporto e Sperimentazione Navale (CSSN) basin of the Italian Navy, and in Ravenna (Italy).