An Efficient Multi-Vehicle Multi-Criteria Mission Planning and Control System for Autonomous Underwater Vehicles

In their study, Tavana and Bourgeois (2010) proposed a multi-criteria decision analysis model that considered dynamic and episodic phenomenon on the surface of the ocean and provided specific navigation plans. They showed that the transect for an autonomous underwater vehicle (AUV) includes not only the desired horizontal path, but the depth range that the vehicle will operate in. They argued that the current models should be extended to include considerations that change vertically, i.e. with different ocean depths. They also suggested expansion of the current models to cooperative teams of AUVs and showed that working together will allow underwater vehicles to complete tasks that could not be completed by a single vehicle. This study extends their model by (1) reducing the number of judgments required to generate the navigation scores within the decision region, (2) considering ocean depth and finding the navigation scores for the ocean surface and interior, and (3) developing a model which derives an optimal allocation of multiple vehicles to various locations within the decision region. The proposed framework is an efficient multi-vehicle multi-criteria mission planning and control system that considers ocean phenomenon on the surface and in the interior and provides an optimal allocation of vehicles with respect to the stated objective and subjective mission goals