Abstract
This paper investigates the unmanned aerial vehicle (UAV)-mission planning problem (MPP) in which one needs to quickly find a good plan/schedule to carry out various tasks of different time windows at various locations using a fleet of fixed-winged heterogeneous UAVs. Such a realistic and complex UAV-MPP is decomposed into two sub-problems: flight path planning and task scheduling. A graph construction and search algorithm is developed for the flight path generation. For the task scheduling problem, a new hybrid algorithm based on heuristic has been proposed: (1) small-to-medium sized problem — heuristics for task assignment and all permutations for sequencing, and (2) large sized problem — heuristics for both task assignment and sequencing. The proposed algorithms have been implemented and tested. Numerical experimental results show that the proposed algorithm is very efficient and can effectively solve relatively big problems.
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