Method and device for distributing multiple unmanned aerial vehicles to perform multiple tasks

Abstract

The embodiment of the invention provides a distribution method and device of multiple unmanned aerial vehicles for executing multiple tasks. The method comprises steps of acquiring position information of multiple unmanned aerial vehicles and target points, and moving parameters of the unmanned aerial vehicles and wind fields; according to the position information and a preset genetic algorithm, constructing an initial population, wherein each chromosome in the initial population comprises the European type flight path of the quantity of the unmanned aerial vehicles; according to the initial population and the moving parameters, determining the flight states of the unmanned aerial vehicles and flight time for finishing the track segments of the European paths, and according to the flight time and an MUAV-VS-EVRP model, acquiring all unmanned aerial vehicle task finishing time corresponding to the chromosomes; and based on the genetic algorithm, carrying out crossing and variation on the chromosomes in the populations, and after achieving the preset iteration times, selecting the chromosome with the shortest unmanned aerial vehicle task finishing time as the task distribution scheme of the unmanned aerial vehicles. According to the invention, by combining the unmanned aerial vehicle planning problem and the actual flight environment of the unmanned aerial vehicles, an optimal flight path scheme obtained through the planning is allowed to be superior to the unmanned aerial constant speed scheme.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of unmanned aerial vehicles, and in particular to a method and device for distributing multiple tasks performed by multiple unmanned aerial vehicles. Background technique [0002] At present, UAV (Unmanned Aerial Vehicle) has a wide range of applications in the military and civilian fields, and can complete various types of tasks such as target reconnaissance, target tracking, intelligence collection, post-earthquake rescue, and geological exploration. For example, when multiple UAVs cooperate to reconnaissance targets, it is necessary to allocate the target reconnaissance to each UAV most reasonably, and plan the optimal flight path for it. This problem is a joint optimization problem of task allocation and trajectory planning subject to multi-factor constraints, and it is also a non-deterministic problem. [0003] With the deepening of UAV research, environmental factors are graduall...

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Problems solved by technology

[0005] An object of the embodiments of the present invention is to solve the problem that the model cannot accurately simulate the actual motion state of the UAV due to the fact that the speed of the UAV is set to be constant when performing track planning in the prior art, and thus cannot give the best result. good track planning

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