Research on Real-Time Mission Planning for Multi-UAV

With the wide application of UAVs in various industries, solving the complex multi-UAV multi-target problem becomes crucial. The assignment and task planning of multi-UAV and multi-target usually need to consider two scenarios. First, before the UAV executes the task, the number and location of the target points need to be determined. It is equivalent to matching UAVs in a situation where the need is determined. Second, in the process of UAV flight, it is necessary to take into account the existing range of the UAV, the number and position of the changed mission points and carry out real-time UAV mission planning. This paper presents a multi-UAV multi-target collaborative task planning algorithm that takes into account these two scenarios. An integer programming algorithm is used to assign target points, and the constraint condition is the shortest range of UAV. The ant colony algorithm is used to plan the path of a single UAV. In this paper, the UAV delivery of disaster relief materials is taken as an example to carry out mathematical modeling and calculate the algorithm. The simulation process starts from the initial location of the UAV at the airport. After a period of flight, the UAV’s voyage information and target location information are updated to carry out real-time mission planning for the UAV. The maximum range of a single UAV is set at 30,000. The simulation results show that the total path length of four UAVs in pre-mission planning is 70,006.49, and the longest path of a single UAVs is 20645.15. In real-time mission planning, the total path length of four UAVs is 43,633.44, and the longest path of a single UAVs is 14,413.56. Over the course of the entire mission, the total path length of the four UAVs is 54,504.00, and the longest path of a single UAV is 16,434.74. The simulation results show that the solution method designed in this paper is efficient and can realize the real-time path dynamic planning of multi-UAV.