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\begin{document}

\title{Pose-graph underwater Simultaneous Localization And Mapping for
autonomous monitoring by means of optical and acoustic sensors}



\author[1]{Alessandro Bucci}%
\author[1]{Alessandro Ridolfi}%
\author[1]{Benedetto Allotta}%
\affil[1]{Universita degli Studi di Firenze Dipartimento di Ingegneria Industriale}%


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  \date{June 13, 2024}


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\begin{abstract}
Modern mobile robots require precise and robust localization and
navigation systems to achieve mission tasks correctly. In particular, in
the underwater environment, where Global Navigation Satellite Systems
(GNSSs) cannot be exploited, the development of localization and
navigation strategies becomes more challenging. Maximum A Posteriori
(MAP) strategies have been analyzed and tested to increase navigation
accuracy and take into account the entire history of the system state.
In particular, a sensor fusion algorithm relying on a MAP technique for
Simultaneous Localization and Mapping (SLAM) has been developed to fuse
information coming from a monocular camera and a Doppler Velocity Log
(DVL) and to consider the landmark points in the navigation framework.
The proposed approach can guarantee to simultaneously locate the
vehicle, thanks to the onboard sensors, and map the surrounding
environment with the information extracted from the images acquired by a
bottom-looking optical camera. Optical sensors can provide constraints
between the vehicle poses and the landmarks belonging to the observed
scene. The DVL measurements have been employed to solve the unknown
scale factor and to guarantee the correct vehicle localization even in
absence of visual features. After validating the solution through
realistic simulations, an experimental campaign at sea was conducted in
Stromboli Island (Messina), Italy. In conclusion, an algorithm, which
works with the Poisson surface reconstruction method to obtain a smooth
seabed surface, for mesh creation has been developed.%
\end{abstract}%



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