A fuzzy logic resource optimizer for a fleet of autonomous vehicles in low-bandwidth conditions

Complex, collaborative maneuvers by a fleet of autonomous underwater vehicles (AUVs) requires the dynamic management of limited time and energy resources at both fleet and individual vehicle levels. The supervisor module presented in this paper attempts to meet this need for a dynamic resource optimizer. Employing linear equivalent fuzzy logic control systems (LEFLC's), this supervisor module optimizes the use of resources both fleet-wide and on each individual AUV through two components. The first component is decentralized across the fleet, and manages time and energy resources on each individual AUV while still accounting for changes in the density of mine-like objects (MLOs). The second component is centralized on the fleet leader, and manages time and energy resources for the entire fleet. Through the employment of the supervisor module described in this paper, the use of time and energy resources is optimized, resulting in faster, more efficient mine-countermeasure (MCM) missions that attain higher confidence of identified MLOs.