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The development of precise and robust navigation strategies for Autonomous Underwater Vehicles (AUVs) is fundamental to reach the high level of performance required by complex underwater tasks, often including more than one AUV. One of the main factors affecting the accuracy of AUVs navigation systems is the algorithm used to estimate the vehicle motion, usually based on kinematic vehicle models and linear estimators. A precise and reliable navigation system is indeed fundamental to AUVs: the Global Positioning System (GPS) signal is not available underwater, thus making it very hard to know the position of the vehicle in real-time. In this paper, the authors present an innovative navigation strategy specifically designed for AUVs, based on the Unscented Kalman Filter (UKF). The new algorithm proves to be effective if applied to this class of vehicles and allows us to achieve a satisfying accuracy improvement compared to standard navigation algorithms. The proposed strategy has been experimentally validated using the navigation data acquired in suitable sea tests performed in Biograd Na Moru (Croatia) in the framework of the FP7 European ARROWS project tests performed during the Breaking the Surface 2014 (BtS 2014) workshop. The vehicles involved are the two Typhoon AUVs, developed and built by the Department of Industrial Engineering of the University of Florence within the THESAURUS Tuscany Region project for exploration and surveillance of underwater archaeological sites. The experiment, described in the paper, was performed to preliminary test the cooperative navigation between these AUVs. The new algorithm has been initially tested offline, and the validation of the proposed strategy provided accurate results in estimating the vehicle dynamic behaviour

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Abstract-This paper addresses localization of autonomous underwater vehicles (AUVs) from acoustic time-of-flight measurements received by a field of surface floating buoys. It is assumed that measurements are corrupted by unknown-but-bounded errors, with known bounds. The localization problem is tackled in a set-membership framework and an algorithm is presented, which produces as output the set of admissible AUV positions in a three-dimensional (3-D) space. The algorithm is tailored for a shallow water situation (water depth less than 500 m), and accounts for realistic variations of the sound speed profile in sea water. The approach is validated by simulations in which uncertainty models have been obtained from field data at sea. Localization performance of the algorithm are shown comparable with those previously reported in the literature by other approaches who assume knowledge of the statistics of measurement uncertainties. Moreover, guaranteed uncertainty regions associated to nominal position estimates are provided. The proposed algorithms can be used as a viable alternative to more traditional approaches in realistic at-sea conditions.

We experimentally prove high-speed underwater optical wireless transmission over 2.5 m distance, using different bit rates and modulation schemes. The system uses two low-cost Light Emitting Diodes (LEDs) arrays as optical transmitter and an avalanche photodiode module as receiver. The measurements are taken using an outdoor water tank having 3.3 m diameter, where two waterproof boxes containing the transmitter and the receiver are fixed underwater at the inner borders. We test 6.25 Mbit/s with Manchester coding, 12.5 Mbit/s with NRZ 8b/10b coding and 58 Mbit/s with Discrete Multitone modulation. Bit Error Rate measurements are collected over several hours under typical summer sunlight illumination conditions. In all the experimental conditions we achieve error free transmission

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A cooperative navigation procedure for a team of autonomous underwater vehicles (AUVs) is described and validated on experimental data. The procedure relies on acoustic communication networking among the AUVs and/or fixed acoustic nodes, and it is suitable as a low-cost solution for team navigation. Embedding the acoustic localization measurements in the communication scheme causes delays and sometimes loss of acoustic data, depending on acoustic propagation conditions. Despite this drawback, the results obtained show that on-board localization estimates have an error of the order of few meters, improving the overall navigation performance and leading the system towards long-term autonomy in terms of operating mission time, without the need of periodic resurfacings dedicated to reset the estimation error. The data were collected during the CommsNet ’13 experiment, led by the NATO Science and Technology Organization Center for Maritime Research and Experimentation (CMRE), and the Breaking The Surface ’14 workshop, organized by the University of Zagreb

Given two control Lyapunov functions (CLFs), a "merging" is a new CLF whose gradient is a positive combination of the gradients of the two parents CLFs. The merging function is an important trade-off since this new function may, for instance, approximate one of the two parents functions close to the origin, while being close to the other far away. For nonlinear control-affine systems, some equivalence properties are shown between the control-sharing property, i.e. the existence of a single control law which makes simultaneously negative the Lyapunov derivatives of the two given CLFs, and the existence of merging CLFs. It is shown that, even for linear time-invariant systems, the control-sharing property does not always hold, with the remarkable exception of planar systems. The class of linear differential inclusions is also discussed and similar equivalence results are presented. For this class of systems, linear matrix inequalities conditions are provided to guarantee the controlsharing property. Finally, a constructive procedure, based on the recently-considered "R-functions", is defined to merge two smooth positively homogeneous CLFs. Index Terms-Composite control Lyapunov functions; stabilizability of linear differential inclusions.