Research On UAV Flight Path Planning Based On Swarm Intelligence Algorithm

In recent years, the development of unmanned aerial vehicle industry is very rapid. UAVs have opened up a broad market space in both military and civial fields. The trajectory planning system is the key technology that guarantees UAV to achieve autonomous flight, more and more attention has been focused on it by professional scholars. This paper proposes related comments and suggestions for the problem of path planning system, Based on the analysis of the existing swarm intelligence algorithm. The improved algorithm is applied in the course of UAV’s flight path planning. Simulation and analysis of the two planning algorithms proposed in this paper are carried out. And it draws the conclusion of the simulation. The main research contents include:(1) In this paper, the existing algorithm of UAV flight path planning and mainstream research direction of swarm intelligence algorithm is studied.(2) The paper established mathematical model of threat constraint of UAV performance constraints and terrain models for route planning on UAVs. Using the grid method and route planning to search a digital map processing map. A comprehensive cost evaluation model UAV flight is established.(3) Analysis the result of the standard ant colony algorithm which applied to unmanned flight path planning process problems. Take suggestions to improve the algorithm for the corresponding circumstances. Refresh algorithm implementation process and the encoding method.(4) Proposed genetic-particle hybrid swarm algorithm. It is designed for UAV flight path planning tasks, and improves the UAV flight path planning algorithm convergence speed effectively.(5) In this paper, the two algorithms are analysis by Matlab simulation, The simulation results were compared and analyzed the effect of planned.