Path Planning for UAV with Constrained conditions Based on Ant Colony Algorithm

In order to improve UAV's operational efficiency and survival probability, the optimal path of an UAV should be designed before the UAV performs a mission. This paper applies UAV's constrained conditions to the search strategies of ant colony and use a new evaluation method of path's cost. The algorithm's state transformation rules and pheromone updating rules are improved. These make its convergence speed and global searching ability enhanced remarkably. The simulation results show that this method can get a flight path which can avoid threats effectively in a short time and is a more efficient path planning method