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A Behavior-Based Mission Planner for Cooperative Autonomous Underwater Vehicles

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Due to its applications in marine research, oceanographic, and undersea exploration, autonomous underwater vehicles (AUVs) and the related control algorithms recently have been under intense investigation. In this work, we address target detection and tracking issues, proposing a control strategy that is able to benefit from the cooperation among robots within the fleet. In particular, we introduce a behavior-based planner for cooperative AUVs, proposing an algorithm that is able to search and recognize targets in both static and dynamic scenarios. With no a priori information about the surrounding environment, robots cover an unknown area with the goal of finding objects of interest. When a target is found, the AUVs’ goal is to classify (fixed target) or track (mobile target) the target, with no information about target trajectory and with formation constraints. Results demonstrate the good overall performance of the proposed algorithm in both scenarios.
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  • The Marine Technology Society Journal is the flagship publication of the Marine Technology Society. It publishes the highest caliber, peer-reviewed papers on subjects of interest to the society: marine technology, ocean science, marine policy and education. The Journal is dedicated to publishing timely special issues on emerging ocean community concerns while also showcasing general interest and student-authored works.
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