| Driven by e-commerce,the business volume of logistics enterprises is growing rapidly,but the major logistics enterprises are generally facing the "last kilometer" problem of rural logistics.The solution of UAV distribution is generally favored by major logistics enterprises,but there are still some technical bottlenecks that hinder the further development of logistics UAV.This paper focuses on one of the typical problems,which is the path planning of UAV distribution.First of all,this paper studies the necessary theories of UAV path planning,including the flying environment of UAV,mathematical principle of path planning,path representation and the modeling theory of digital elevation map,focusing on the representation of static or moving sudden obstacles based on digital elevation map.Then,based on the actual task flow of UAV path planning,the offline static path Pre-planning model and online dynamic path correcting model are established.On this basis,the paper considers the error correcting problem of the UAV under the condition of the limited positioning accuracy of the navigation system,further expands the consideration factors of the UAV in the path planning,and enhances the robustness and reliability of the model.At the same time,in order to improve the accuracy and speed of calculating the UAV path,this paper redesigns the solving-algorithm of the UAV path planning model.This paper studies and analyzes the advantages and disadvantages of various classical algorithms for UAV path planning.On this basis,we select the latest lion swarm optimization as the basic algorithm,combined with quantum local search and elite reverse learning strategy to further modify it.Then through the standard test function,the modified algorithm is compared with the classical swarm intelligence algorithm,such as genetic algorithm and particle swarm algorithm,to verify the performance of the modified algorithm.The experiment shows that the modified lion swarm optimization has better performance in solving optimization problems.Finally,this paper designs the specific simulation parameters of model,and uses the modified lion swarm optimization to solve the path planning model,in order to test the rationality and reliability of the logistics UAV path calculated by the model and algorithm.The experiment shows that the model proposed in this paper successfully solves the problem of the logistics UAV path planning,and the path calculated by algorithms successfully completes the avoidance of sudden static or moving obstacles and corrects the path error in time.At the same time of simulation experiment,this paper further compares the performance of modified lion swarm optimization with genetic algorithm,particle swarm optimization and lion swarm optimization in solving the actual optimization problem.The experiment shows that the modified lion swarm optimization still has outstanding performance in solving the problem of logistics UAV path,its convergence speed is faster,and the probability of falling into the local optimal solution is lower. |
