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
Attitude estimation is a crucial aspect for navigation and motion control of autonomous vehicles. This concept is particularly true in the case of unavailability of localization sensors, when navigation and control rely on dead reckoning strategies; in this case, indeed, the orientation estimate is also used along with speed measurements to update the position estimate. Among the different approaches proposed in the literature, the de facto state of the art in this field is represented by non-linear complementary filters: they fuse the measurements of angular rate obtained through gyroscopes and a measurement of gravity and Earth's magnetic field vectors respectively obtained through accelerometers and magnetometers. The described work is focused on an attitude estimation strategy for Autonomous Underwater Vehicles (AUV). The proposed novelty includes the identification of some critical issues that arise when AUV attitude estimation algorithms are applied in practice: they are mainly due to the use of low accuracy low cost Micro-Electro-Mechanical Systems (MEMS) sensors and on different sources of magnetic disturbances. Some strategies to overcome the identified issues are proposed, including the integration of a single axis Fiber Optic Gyroscope (FOG), that ensures a considerable performance improvement with a moderate cost increase. The proposed strategies for detection of issues and sensor fusion have been experimentally tested and validated in a real application scenario estimating the attitude of an AUV performing a lawn mower path. The expected performance improvement is confirmed; the obtained results are described and analyzed in the paper.
a b s t r a c tA detailed description of adhesion is crucial in tribology, vehicle dynamics and railway systems, both theoretically and practically. However, an accurate adhesion model is quite hard to develop because of the complex and non-linear behaviour of the adhesion coefficient and the external unknown contaminants which are present between the contact surfaces. The problem becomes even more complicated when degraded adhesion and large sliding between the contact bodies (for instance wheel and rail) occur.In this paper the authors describe an innovative adhesion model aimed at increasing the accuracy in reproducing degraded adhesion conditions in vehicle dynamics and railway systems; the new approach turns out to be quite suitable also for multibody applications (fundamental in this research topic). The model studied in the work considers some of the main phenomena behind the degraded adhesion: the large sliding at the contact interface, the high energy dissipation, the consequent cleaning effect on the contact surfaces and, finally, the adhesion recovery due to the external unknown contaminant removal.The new adhesion model has been validated through experimental data provided by Trenitalia S.p.A. and coming from on-track tests carried out in Velim (Czech Republic) on a straight railway track characterised by degraded adhesion conditions. The tests have been performed with the railway vehicle UIC-Z1 equipped with a fully-working Wheel Slide Protection (WSP) system.The validation showed the good performances of the adhesion model both in terms of accuracy and in terms of numerical efficiency; high computational performances are required to implement the developed model directly online within more general and complex multibody models (e.g. in MatlabSimulink and Simpack environments). In conclusion, the adhesion model highlighted the capability of well reproducing the complex phenomena behind the degraded adhesion.
The Mechatronics and Dynamic Modelling Laboratory of the Department of Industrial Engineering, University of Florence, as a partner of THESAURUS (Italian acronym for ‘TecnicHe per l’Esplorazione Sottomarina Archeologica mediante l’Utilizzo di Robot aUtonomi in Sciami’) project, has developed an innovative low-cost, multirole autonomous underwater vehicle, called Tifone. This article deals with the adopted methodologies for the autonomous underwater vehicle design: in particular, the main focus of this study is related to its propulsion system. According to the expected performances and requirements of THESAURUS project, the vehicle has to maintain good autonomy and efficiency (typical features of an autonomous underwater vehicle), with high manoeuvrability and hovering capabilities, which are more common of remotely operated vehicles. Moreover, cooperative underwater exploration and surveillance involve the use of a swarm of vehicles. In particular, the optimization of costs versus benefits is achieved through the design of a fleet of three multirole vehicles. Each autonomous underwater vehicle has five controlled degrees of freedom, thanks to four thrusters and two propellers: in this article, the preliminary design criteria concerning the vehicle and the design and testing of its actuation system are described
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