In this paper,a multi-heuristic ant colony optimization algorithm is proposed for the route planning of the unmanned aerial vehicle ( UAV) in complex environments. In the algorithm,the distance and the threat distribution between the current UAV position and the candidate one,as well as between the candidate position and the target one,are designed as the multi-heuristic information in the state transition of ants to guide their search behaviors. Moreover,the convergence of the ant colony optimization algorithm is analyzed,and the route smoothing and online route replanning methods are presented respectively for the unfeasible route and the pop-up threats in the task region. Simulation results show that the proposed methods can effectively enhance the route planning ability of the ant colony optimization algorithm and improve the speed and precision of the convergence,thus achieving the optimal route.