Method for realizing unmanned aerial vehicle group formation reconstruction based on genetic algorithm and Dubins algorithm

Abstract

The invention designs a method for realizing unmanned aerial vehicle group formation reconstruction based on a genetic algorithm and a Dubins algorithm. The method specifically comprises the followingsteps: numbering unmanned aerial vehicles, establishing a position matching relation of each unmanned aerial vehicle in a new formation, and consequently completing coding of chromosomes; improving the Dubins algorithm, building an air route planning model, evaluating distance of completing reconstruction flight by a wing unmanned aerial vehicle; and allocating a reconstruction target position for each unmanned aerial vehicle based on the genetic algorithm. In the method provided by the invention, formation reconstruction is divided into task allocation and air route planning, relative to theexisting formation reconstruction algorithm, more stable air routes can be obtained, moreover, speed range and radius of turning circle of the unmanned aerial vehicles are considered, the air routesgenerated can be more rational and can be used in actual application more easily. In the method provided by the invention, by a mode of limiting variation and intersecting, each unmanned aerial vehicle is guaranteed to have a position allocated, situations of missing of allocation and allocating in mistake can be prevented, and quality of task allocation is improved further.

Description

technical field [0001] The invention relates to route planning and target allocation of a UAV swarm during autonomous flight, and specifically designs a route construction method for UAV swarm formation reconstruction. Background technique [0002] With the development of UAV technology, the role of UAV in combat is becoming more and more prominent. The overall performance of multiple UAVs forming a formation to perform tasks such as cooperative detection, reconnaissance, and combat has been greatly improved compared with a single UAV. Multi-unmanned aerial vehicles (UAVs) formation flying to perform cooperative reconnaissance and combat missions can improve the success rate of a single combat mission to a certain extent, thus causing a research boom in various countries on multi-aircraft formation flying. During the formation flight of the UAV group, facing different mission requirements and threat types, and in order to obtain a better advantage against the enemy in air c...

AI Technical Summary

Problems solved by technology

However, these algorithms often ignore the performance constraints of UAVs in the process of use, such as the turning radius limit and speed limit of UAVs, etc., resulting in the calculated path may not be really used in practice

At the same time, when considering the optimization parameters, these algorithms usually take the shortest time or the shortest path as the optimization goal, but they do not take into account the speed and direction of the UAV when it reaches the target point.

As a result, even if the drone can form a preset formation at the moment of reaching the target point, the formation will collapse due to the difference in speed

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