Path planning for unmanned aerial vehicle based on genetic algorithm

Path planning has always been a crucial issue for UAV. The UAVs path planning in multiple missions involves the solution of an optimization problem. Genetic algorithms (GAs) are well applied to solve such problems as a stochastic search method. In this paper, a new method based on genetic algorithm is presented to generate path for UAV in the existence of unknown obstacle environments. The path planning model is based on 2D digital map, and an adaptive evolutionary planner is adopted based on a set of criteria to generate path online to avoid being detected by ground surveillance radar sites. Simulation studies are carried out to verify the effectiveness of the proposed algorithm. We believe the GA algorithm may be of help in the future reseach direction of UAV path planning problem.