Path Planning For UAV Based On Ant Colony Potential Field Hybrid Algorithm

With the progress of society and the development of science and technology,the demand of UAV is increasing.For its excellent performance experience,the UAV has been widely used in military and civilian fields in recent years.The path planning is not only the premise of UAV autonomous flight of UAV,but also the key to successful completion of designated missions.Simultaneously,it is an indispensable research content of UAV development.The path planning issues become challenging,Due to the complexity of flight environment and so many constraints on the UAV flight path planning,which makes the path planning problem very challenging.For this problem,the usual approach is to use an algorithm for path planning only.However,one or more problems always arise during planning.In this paper,the ant colony potential field hybrid algorithm is used to plan the flight path of UAV.The main research content includes:First of all,the algorithm is improved based on the max-min ant system and the intelligent ant algorithm in this paper,for the ant colony algorithm is prone to search stagnation and the time required for planning is longer.The improved methods are as follows: A node guidance factor is introduced in the state transition probability of the algorithm to reduce the waste of resources and accelerate the speed of ants reaching the target point;the path node adaptive selection strategy is adopted in the selection of flight nodes,to prevent search stagnation and speed up the convergence;in terms of pheromone concentration,the node pheromone threshold adjustment strategy and the pheromone volatilization factor intelligent adjustment strategy are used to speed up the convergence;a QC quality control mechanism is proposed to help the algorithm jump out of the local optimum.Finally,the simulation experiment shows that this method solves the problem of algorithm search stagnation and accelerates the convergence speed of the algorithm.Secondly,for the existing path concussion problem and local minimum problem of the artificial potential field method,this paper improves them from two aspects.First,a guide factor which is the relative distance of the UAV between the current point and the target point is added to the repulsive field function.Secondly,the repulsive force generated by threats on the UAV is decomposed into two forces.One of the componentis in the same direction as the gravity generated by the target point to the UAV,the direction of the other component is tangent to the boundary of the circle where the obstacle is covered and the angle is acute.Finally,the simulation experiment shows that the method can effectively solve the problems encountered by the algorithm and has certain feasibility.Finally,the ant colony potential field hybrid algorithm is proposed.The hybrid algorithm forms a new heuristic information function by introducing the potential field force to the ant colony algorithm.It also introduces the potential field force adjustment factor minimum limit strategy and the pheromone disturbance adjustment mechanism to prevent the algorithm from falling into a local optimum.The simulation results show that the hybrid algorithm can give full play to the advantages of different algorithms and solve the problems of global and online path planning of UAV.It's feasible.