Application of Pre-evolution Genetic Algorithm in Fast Path Planning for UCAV

Abstract

Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for unmanned combat aerial vehicle (UCAV), an approach of fast path planning based on Voronoi diagram and pre-evolution genetic algorithm (PEGA) is proposed, which makes use of the principle of hierarchical path planning. First the Voronoi diagram is utilized to generate the initial paths and calculate the weight of the paths by considering the constraints. Then the optimal path is searched by using PEGA. Multiprocessors parallel computing techniques are used for PEGA to improve the traditional genetic algorithm and the optimal time is greatly reduced. Simulation results verify that the method of path planning is more favorable in the real-time operation. It can improve the adaptability of dynamic battlefield and unexpected threats for UCAV.