Coverage Path Planning of UAV Cluster Based on Independent PPO in Complex Environment

Unmanned aerial vehicle (UAV) clusters have been widely applied in fields such as terrain coverage, mapping, and natural disaster tracking. To address the challenges in UAV clusters coverage path planning (CPP), this paper designs a coverage path planning approach for UAV clusters based on the independent proximal policy optimization (IPPO) algorithm. This method integrates both local and global information, effectively improving task completion efficiency. It also addresses the constraints of battery endurance and collision avoidance in complex three-dimensional environments, ensuring the safety and coordination of navigation. Validation results demonstrate that the proposed algorithm achieves nearly complete area coverage within a short time, outperforming existing methods in terms of adaptability, stability, and efficiency.