Cooperative Task Assignment and Track Planning For Multi-UAV Attack Mobile Targets

This paper proposes a system framework for solving the problem of multi-UAV cooperative task assignment and track planning for ground moving targets. For the combinatorial optimization model, it is solved by a new particle swarm optimization algorithm based on guidance mechanism. In order to plan an effective track for the target more rapidly, a new ant colony optimization algorithm based on adaptive parameter adjustment and bidirectional search is proposed. Furthermore, in the case of target movement, a method of the predicted meeting point is proposed to solve the problem that the moving point cannot be used as the target point of the track planning algorithm. In addition, the track planning problem in the UAV tracking mode is also considered. An online re-planning method is proposed for time-sensitive uncertainties. Finally,the simulation results show that compared with other algorithms, the proposed method can not only effectively plan a reasonable track, but also solve the uncertainty problem, and obtain the optimal task allocation plan, which improves the multi-UAV cooperative combat capability.

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