| Citation: | KE Z J，XU G N，CAI R，et al. Optimization of multi-mission scheduling for swarm UAVs with charging platform[J]. Journal of Beijing University of Aeronautics and Astronautics，2025，51（8）：2782-2791 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0414
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The swarm unmanned aerial vehicles (UAVs), characterized by their large quantity, low cost, and unified scheduling, have broad application prospects. Unified scheduling is a focal point and challenge in swarm UAVs research, aiming to the optimal allocation of tasks and resources. Current scheduling research primarily focuses on small-scale, short-term scenarios without considering complex scenarios such as mid-operation charging. However, for future multi-task and long-term applications, scheduling optimization must account for such factors. An improved mission scheduling method for swarm UAVs based on a unified scheduling model and an improved genetic algorithm was proposed. First, the wireless charging platform resources were incorporated into the UAV working environment, and the working scenario was modeled systematically. Then, the genetic algorithm was used to optimize the mission and charging platform resource allocation. Finally, the proposed method was tested for validation using simulated scenarios. Test results show that the method proposed can better adapt to changes in missions, environment, and resources, showing good performance even for large-scale swarm UAVs.
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