Research On Cooperative Mission Planning For Multi-unmaned Aerial Vehicle

Multi-UAV cooperative mission planning is the problem of multi-UAV control and optimization in a certain complex obstacle environment.It includes two steps: target assignment and path planning for multiple UAVs.Target assignment is to assign each sub-target with low cost and high efficiency,so as to give full play to the advantages of multiple UAVs;Path planning is to find the optimal or relative optimal path from the starting point to the target point in the working environment of obstacles and threat areas for UAVs,which is to improve the control energy of UAVs.Force is one of the keys to autonomous flight.In the multi-UAV cooperative target assignment problem,most of the current researches focus on single target solution or multi-target transformation for the purpose of minimum flight time or cost.However,it is urgent to optimize the multi-target simultaneously for the multi-UAV mission.Problems to be solved.Based on the analysis of genetic algorithm,an improved multi-objective genetic algorithm is proposed to solve multi-UAV target assignment.The initial population is generated by random method to ensure the dispersion and uniformity of Pareto optimal solution set,and the relative optimal strategy is introduced to determine the final solution set.Artificial potential field method is selected to solve the problem of multi-UAV collision avoidance and path planning.Conventional artificial potential field method has the characteristics of high efficiency,high security and high real-time,but the traditional methods have the defects of unreachable targets,narrow channels and jitter problems,and the planned path is not smooth enough to adapt to three-dimensional complex environment.In this paper,an optimized artificial potential field method is proposed,which can be improved as follows:(1)distance factor is introduced to compensate for the shortcomings of traditional artificial potential field method which is easy to fall into local extreme points and can not reach the target;(2)dynamic step adjustment method is proposed to solve the problem of planned track jitter to obtain smoother path;(3)modification The repulsive force function is adopted to take the repulsive influence of UAV’s companion into consideration,so as to achieve cooperative anti-collision.Based on the above algorithm,the simulation of target assignment and route planning for multiple UAVs is carried out.In the aspect of target allocation,the detection,jamming efficiency and flight cost of UAV are taken as the targets and the multi-objective genetic algorithm is adopted.Compared with the traditional singleobjective optimization,the improved method proposed in this paper can make the mission more efficient and the flight cost as small as possible,which proves the effectiveness of the optimization model and algorithm.In the aspect of track planning and anti-collision,the complex environment of multiple UAVs at the same altitude is simulated firstly,and then the narrow channel of multiple UAVs at the same vertical plane is simulated.Finally,the three-dimensional complex environment is introduced,especially the climbing strategy is added to improve the efficiency of three-dimensional anti-collision.Experiments show the effectiveness of the artificial potential field method.In this paper,the cooperative mission planning of multiple UAVs is studied and explored,and the corresponding optimization algorithm is proposed to solve the problem.This paper has certain theoretical value and application value for cooperative control and planning of multiple UAV systems and autonomous flight.