Abstract

A recent concern in marine robotics is to consider the deployment of fleets of autonomous underwater vehicles (AUVs) and autonomous surface vehicles (ASVs). Multiple vehicles with heterogeneous capabilities have several advantages over a single vehicle system, and in particular the potential to accomplish tasks faster and better than a single vehicle. This paper addresses in this context the problem of underwater targets localization. A systematic and exhaustive coverage strategy is not efficient in terms of exploration time: it can be improved by making the AUVs share their information to cooperate, and optimize their motions according to the state of their knowledge on the target localization. We present techniques to build environment representations on the basis of which adaptive exploration strategies can be defined, and define an architecture that allows information sharing and cooperation between the AUVs. Simulations are carried out to evaluate the proposed architecture and the adaptive exploration strategies.

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