This paper discusses the development and testing of a flexible genetic algorithm (GA)-based system used for tasking a team of unmanned aerial vehicles (UAVs) to complete a coordinated surveillance mission. The GA development, laboratory testing of the GA to ensure convergence to a \good" solution, integration testing with two ground stations, and the field testing of the algorithms are explained. The algorithm was found to be robust and flexible enough to work in various settings with different UAV types and ground stations.

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