Low-cost safe path planning and exit scheduling of multi-UAV aerial refueling based on swarm intelligence

Aerial refueling technology is a crucial means of extending unmanned aerial vehicles (UAVs) mission duration and expanding operational range, garnering extensive attention. However, planning safe and cost-effective refueling routes for multiple UAVs in complex three-dimensional airspace, and achieving efficient and orderly egress after mission completion, still face technical challenges such as inadequate path safety and low egress scheduling efficiency. To address these challenges, this paper proposes a multi-agent hierarchical collaborative optimization framework that simulates group competition and cooperation to achieve task allocation and path coordination. By integrating factors such as path length, threat sources, air turbulence, altitude-dependent energy consumption, and turning loss, a multi-dimensional cost function is constructed, forming a comprehensive trajectory optimization model for UAV aerial refueling missions. Based on flight landing scheduling (FLS) theory, a dynamic time window allocation and conflict resolution mechanism is introduced, establishing a two-stage optimization architecture of ”path planning-safe egress.” Simulation results indicate that, compared to several mainstream meta-heuristic algorithms, the proposed method achieves superior path quality and higher scheduling efficiency under complex conditions, reliably accomplishing low-cost, coordinated multi-UAV refueling and safe egress operations.