In this article we present and discuss a cooperative localization and navigation system based on the Extended Kalman Filter specifically designed to meet the requirements of the underwater environment. These lead us to consider a SLAM-like scheme in which some other Autonomous Underwater Vehicles (AUVs) play the role of mobile environment features and range measurements are used as external data. Own "recent" navigation data and some minimal communicated data by other AUVs are used to consistently update pose estimates and error covariances of relevant vehicles. A number of simulation and experimental results are presented to illustrate the approach.
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