Integrated MCM missions using heterogeneous fleets of AUVs

The capability and cost effectiveness that unmanned underwater vehicles (UUVs) bring to underwater survey, target detection and identification operations has been widely demonstrated and accepted in recent years. However, these operations still rely mainly on pre-planned missions and require a high level of expert human interaction both at the planning and data analysis stages. In this paper, we present an integrated mission approach using heterogeneous fleets of UUVs that provides a series of performance improvements over state-ofthe- art solutions. The approach is formed by a combination of novel automatic target recognition techniques, distributed knowledge representation, and algorithms for autonomous inmission decision making. This results in an increase tempo of operation as well as an improvement in the pertinence of the gathered data whilst reducing the need for expert human input. The benefits of the approach are demonstrated in real in-water trials where vehicles have different capabilities and collaborate to perform a mine hunting clearance process for a user-defined area of the seabed.