Hierarchical Cooperative Path Planning of Multiple UAVs Based on PSO-APF

To address the challenges of local optima, limited adaptability, and suboptimal route efficiency in traditional multi-UAV cooperative path planning algorithms, this paper proposes a Hierarchical PSO-APF(H-PSOAPF)algorithm. By constructing a Lightweight Constraint Fusion Function (LCFF), complex constraint problems, including coverage degree, path length, turn angle limits and inter-drone spacing, are transformed into an unconstrained optimization problem via a penalty function approach. Moreover, a hierarchical structure is adopted to coordinate global path planning and local dynamic adjustment: PSO is employed to generate a globally optimized reference trajectory, while APF conducts real-time local modifications for obstacle avoidance and trajectory smoothing. Simulation results indicate that a runtime reduction of over 80% is achieved compared to PSO, and a 31.3% improvement in computational efficiency is obtained over APF by using the PS O-APF algorithm.