@article{GENERAL,
      author = {Tesei, A and Micheli, M and Vermeij, A and Ferri, G and  Mazzi, M and Grenon, G and Morlando, L and Costanzi, R and  Fenucci, D and Caiti, A and Munafò, A},
      url = {http://library.imarest.org/record/7718},
      journal = {Conference Proceedings of iSCSS},
      title = {An acoustic-based approach for real-time deep-water  navigation of an AUV},
      abstract = {Navigation of Autonomous Underwater Vehicles (AUVs)  remains a challenge due to the impossibility to use radio  frequency signals and Global Positioning System (GPS).  Navigation systems usually integrate different  proprioceptive sensors to estimate the asset and the speed  of the vehicle. In particular, the Doppler Velocity Log  (DVL) is fundamental during the navigation to have an  accurate estimate of the vehicle’s speed. This work  addresses the enhancement of the navigation performance of  an AUV through the development of a Deep Water Navigation  Filter (DWNF). The DWNF is able to work in those scenarios  where traditional navigation sensors show their limits:  e.g., deep waters where DVL bottom lock cannot be achieved,  or areas where the use of traditionally used static and  dedicated beacons is incompatible with the mission  requirements. The proposed approach exploits the concept of  using a network of vehicles cooperatively supporting each  other for their navigation. Several types of measurements  coming from the different nodes (i.e. acoustic positioning  system such as ship-mounted SSBL acoustic positioning  system, USBL, range measurements from the different nodes)  are fused in an Extended Kalman Filter framework with the  odometry data. DWNF pushes forward the idea of using a  network of robotic assets as a provider of navigation  services allowing more flexible and robust operations of  the deployed system.

The approach has been tested at sea  during several experiments. We report here results from  DWNF running successfully in real-time on the NATO  STO-Centre for Maritime Research and Experimentation (CMRE)  vehicles during the Dynamic Mongoose’17  experimentation off the South coast of Iceland (June-July  2017). },
      number = {GENERAL},
      recid = {7718},
      address = {2018-10-02},
}