A Fixed-wing UAV Swarm Coverage Search Path Planning Method Based on Adaptive Evolutionary Ant Colony Algorithm

For the problem of fast dive search in unknown sea area. In this paper, a fixed-wing unmanned aerial vehicle (UAV) swarm coverage search path planning algorithm based on adaptive evolutionary ant colony algorithm is proposed. Firstly, a fixed-wing UAV kinematic model and an environment map model are established according to the mission requirements and environmental constraints. Then the search path planning of the fixed-wing UAV swarm is carried out by the adaptive evolutionary ant colony algorithm. The adaptive evolutionary ant colony algorithm has two methods of setting up the initial pheromone map and two ways of updating the search starting point, so there are four search strategies. The path planning simulation experiments are carried out using different shapes of mission sea area, the results show that the best search strategy is to not use a priori pheromone map and the search starting point is updated by selecting the historical optimal path starting point.