The Study About The Track Planning Of Express Unmanned Aerial Vehicle(UAV) For Intelligent Obstacle Avoidance

Under the background of the coexistence of the two status quo,which are the scientific and technological trend of solving the increasingly prominent "last mile"problem of rural logistics by the express UAV is proposed and UAV express technology is limited in the promotion and application around the whole nation,due to the lack of technology and solutions for the planning of general aviation routes for express UAV,researching the theory and technology of express UAV track planning for intelligent obstacle avoidance is beneficial to implement the promotion and application of UAV express technology and create "smart-technology logistics".Based on the current study status about two-dimensional static track planning scheme for military UAV,a small number of military UAV three-dimensional dynamic real-time track planning schemes and lack the research on the status quo of three-dimensional static and dynamic track planning schemes for express UAV,constraints and target functional models for intelligent obstacle avoidance are established,designing 3D static track planning optimization algorithm based on 3D sparse A-Star search algorithm and 3D dynamic track planning optimization algorithm based on 3D artificial potential field algorithm are proposed in this paper,which aims to achieve optimization goals such as avoiding obstacles by wisdom,improving the practicality of conclusions,reducing costs and completing the general aviation traffic control program.Firstly,the application field,economic feasibility,operation system,etc.of UAV express technology are analyzed to prove that researching tasks of the UAV track planning is of great direction;The UAV track planning system and the mathematics principle of track planning are analyzed to propose the track planning task module,then the six sub-tasks and processes involved in the track planning task are clarified.Secondly,the track planning model for express UAV is built,including planning type(track),track representation(point,line,arc),configuration space(original digital terrain elevation modeling,mountain and weather threat model modeling,2D cubic convolution interpolation smoothing,information fusion,etc.),constraints(7 items),track cost(integrated type).Thirdly,the track planning algorithm is researched based on the algorithm classification and applicability analysis of GA,ANN,PSO,Dijkstra,AC,APF,etc.;The 3D sparse A-Star search algorithm for 3D static track planning(global)of express UAV is researched and designed,which combines traditional A-Star algorithm,sparse search algorithm and dynamic step size algorithm.Based on the analysis about defects of the traditional artificial potential field algorithm,inclouding the local optimal value and unable to reach the deatination,the 3D artificial potential field algorithm for 3D dynamic track planning(partial)of express UAV is studied and designed,which combines the traditional artificial potential field algorithm and the following improvement schemes proposed in this paper:improving the gravitational algorithm to a fixed value,introducing adjustment components to improve the repulsion algorithm and proposing the priority planning strategy.Finally,the effectiveness of the express UAV track planning model,3D sparse A-Star search algorithm and 3D artificial potential field algorithm for intelligent obstacle avoidance are proved with the Matlab simulation platform.Set simulation parameters and compare the optimization effects of A-Star and 3D sparse A-Star search algorithm;Change the simulation parameter values and simulate the optimization effect of 3D sparse A-Star search algorithm in multi-environment;For the static sudden obstacles and sports sudden obstacles,the dynamic real-time obstacle avoidance track optimization effects of artificial potential field algorithm and 3D artificial potential field algorithm are compared;With the above simulation experiments,the effectiveness of the algorithm and model improvement scheme are proved in this paper,which can improve the track planning efficiency.