Unmanned aerial vehicles (UAVs) have been widely used in various fields and have the advantages of low safety factor and low cost. However, due to the limited endurance of the UAV, it is impossible to reach a long distance, a new solution is to use the vehicle to carry and launch the UAV, that is, the collaborative way of the UAV and the vehicle, in order to complete the total time of the minimum as the goal. In this paper, a two-stage algorithm is proposed to solve the path planning problem of UAV-vehicle cooperative operation. In the first stage, the target area is divided using a clustering algorithm to determine the distribution of vehicles. In the second stage, the traditional teaching optimization algorithm HTLBO is designed and improved to improve the search efficiency, and the route of the UAV is obtained in each target area to ensure the optimization of the route. Finally, the experimental results compared with other comparison algorithms show that the vehicle-UAV joint operation model and HTLBO algorithm are feasible and robust, and provide some ideas and references for complex dynamics in various large-scale areas.