Mission planning for UAV swarm air-launched by single carrier aircraft under multiple constraints

Unmanned aerial vehicles (UAV) swarm air-launched by single carrier aircraft can significantly expand the operational range and maximize the collaborative potential of the unmanned swarm system. However, the air-launch paradigm introduces additional constraints and subproblem, which greatly increase the complexity of mission planning and lead to strong input–output coupling among subproblems. To address these challenges, a mission planning model is developed in this study, and the coupling relationships among four interdependent subproblems-release point information determination, task allocation, scheduling, and path planning-are thoroughly analyzed. A self-search differential evolution (SSDE) algorithm is proposed to solve the mission planning problem under multiple constraints and strong coupling. The algorithm incorporates a constraint-guided clustering initialization method to improve the potential feasibility and diversity of the initial population. In addition, a mutation operator embedded with a self-search mechanism is introduced to enhance the ability to escape local optima. Simulation results demonstrate that the proposed SSDE algorithm effectively handles the multi-constraint, strongly-coupled mission planning problem of the air-launched UAV swarm, outperforming conventional algorithms in solution quality.