Intelligent UAV Swarm Planning Based on Undirected Graph Model

The coordination of multiple drones for formation flight and collaborative task execution in the air, known as drone cluster control, has become a key research focus in recent years. Collision avoidance during formation maintenance remains a challenging aspect of cluster control, as traditional cluster control and path planning algorithms struggle to enable individual drones to independently avoid obstacles and maintain formation within the cluster. To address this issue, this paper proposes a cluster modeling method based on an undirected graph, which optimizes the entire model by adding constraints. A distributed system is also utilized to plan the entire cluster, improving the efficiency and robustness of the system and allowing individual drones to execute their flight tasks independently. Experimental verification was conducted in a ROS-based simulation environment, and the results demonstrate that our proposed algorithm effectively maintains the formation of drone clusters with high performance and stability.