Scientific Development Research

With the rapid development of drone technology, autonomous patrol missions in complex environments for UAV swarms have garnered increasing attention. This paper proposes an autonomous patrol strategy for UAV swarms based on path planning and obstacle avoidance collaborative control. The strategy integrates global path planning with local obstacle avoidance algorithms, optimizing the coordination mechanism between drones to ensure both efficiency and safety during patrol operations. The research focuses on solving dynamic obstacle avoidance problems in path planning and enhancing task robustness through multi-drone collaborative control strategies. Experimental results demonstrate that this approach effectively improves the autonomy, flexibility, and obstacle avoidance capability of UAV swarms, providing theoretical foundations and practical support for future autonomous patrol missions.

UAV swarm; Path planning; Obstacle avoidance; Collaborative control; Autonomous patrol