Multi-unmanned aerial vehicle task allocation method based on improved ant colony algorithm

Abstract

The invention discloses a multi-unmanned aerial vehicle task allocation method based on an improved ant colony algorithm, and the method comprises the steps: carrying out the improvement of the ant colony algorithm, and representing that the movement transfer direction of ants of unmanned aerial vehicles is determined by the pheromone concentration of each unmanned aerial vehicle flight path in the movement process; in the task allocation searching process, ants representing the unmanned aerial vehicle intelligently select a path to be traveled in the next step; the path distance calculated byadopting the ant colony algorithm is compared with the linear distance directly calculated between the two points, the shorter distance is selected as the optimal path for the unmanned aerial vehicleto search for the target, meanwhile, the gradient descent method is adopted for optimization to shorten the flight distance of the unmanned aerial vehicle, and the method is suitable for task allocation of multiple unmanned aerial vehicles. The unmanned aerial vehicles can quickly complete tasks and reduce the flight distance. By adopting the technical scheme of the invention, the task completiontime can be reduced, and the flight distance of the unmanned aerial vehicles during task search is shortened.

Description

technical field [0001] The invention belongs to the technical field of multi-UAV task assignment, and relates to a multi-UAV task assignment method based on an improved ant colony algorithm. Background technique [0002] In recent years, multi-UAV cooperative control has become a research hotspot in the UAV field, and task allocation is the guarantee and basis for multi-UAV cooperative control. Task allocation is to reasonably assign the tasks that need to be completed to the team members in the system according to the established goals, so as to achieve the purpose of efficiently executing tasks and optimizing the UAV system. Multi-UAV cooperative task allocation is to decompose a certain combat task into some sub-tasks and assign them to multi-UAV systems according to a set of specific conditions, with the goal of achieving the optimal or suboptimal criterion function. Each UAV in the process is completed separately. The goal is to assign specific goals and action tasks ...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies in the prior art and solve the problems of long time for multi-UAVs to complete tasks and long flight distances of UAVs when searching, the present invention proposes a method for improving the ant colony algorithm, which is suitable for multi-UAVs The task allocation problem of the problem is improved on the basis of the ant colony algorithm, which reduces the time to complete the task and shortens the flight distance when the UAV searches for the task.

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