Distributed biconnectivity-preserving flocking with fast obstacle avoidance for UAV swarms

Obstacles in low-altitude environments force unmanned aerial vehicle (UAV) swarms to frequently alter their flight paths and communication links, which can easily cause network interruptions. It remains a significant challenge for UAV swarms to rapidly traverse obstacle-rich environments while maintaining topological robustness under distributed control. To address this issue, an enhanced flocking algorithm is proposed, incorporating two key innovations: a biconnectivity-preserving force and a rotational repulsive force. By identifying critical neighbors via induced subgraphs, the biconnectivity-preserving force enables each UAV to maintain essential links through local interactions, achieving global biconnectivity. Meanwhile, the rotational repulsive force, whose direction is determined by a novel proximal policy optimization (PPO)-based method, effectively overcomes the limitations of traditional repulsive forces and facilitates rapid obstacle avoidance. Experimental results demonstrate that the proposed method significantly improves both the robustness of the network and the navigation speed in low-altitude obstacle environments compared to existing methods, showing great potential for autonomous systems that require highly reliable communications.