Abstract

Within the project NOPTILUS, a fully functional system/methodology had been developed that allows the cooperative, fully-autonomous navigation of teams of AUVs when deployed in Static or Dynamic Underwater Map Construction (SDUMC) or Dynamic Underwater Phenomena Tracking (DUPT) missions. The key ingredient of this fully functional system/methodology (called the NOPTILUS Planning, Assignment and Navigation Module - NOPTILUS PAN) is an optimal control algorithm - called Parametrized Cognitive Adaptive Optmization - (PCAO) - developed by one of the NOPTILUS partners (CERTH). PCAO is firstly tailored and modified so as to be applicable to the problem of autonomous navigation of teams of AUVs when deployed in SDUMC or DUPT missions. For this purpose, a nonlinear model is developed so as to capture the dynamics of the AUVs, their sensors and the underwater environment. More precisely, the original PCAO-based approach is revised so as to be able to efficiently handle information coming from the localization module, the underwater acoustic communication module, the situation understanding module as well as instructions from the operator. The information coming from these modules is handled by the NOPTILUS PAN module without the need to enter in tedious re-design tasks. Two real-life experiments (involving teams of AUVs deployed in static mapping or simultaneous static mapping and dynamic target taking) demonstrate the efficiency and practicability of the NOPTILUS PAN module.

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