Cooperative Coverage Mission Planning for Multi-UAV Based on the Dual-Ring Dynamic Scheduler

Unmanned aerial vehicles (UAVs) have rapidly advanced in applications, such as disaster response, infrastructure inspection, and smart city systems. However, cooperative coverage mission planning in dynamic environments poses a persistent challenge in balancing global optimization with real-time responsiveness. To address this, we propose a two-stage task allocation framework based on a dual-ring dynamic scheduler. In the centralized planning phase, an enhanced NSGA-II algorithm is developed, incorporating dual-population initialization, path-exchange crossover, and multistrategy mutation. Experimental results demonstrate a 49% improvement in the hypervolume indicator over the baseline NSGA-II, with average reductions of 13.33% and 23.71% in total and maximum execution times, respectively. In the dynamic scheduling phase, we design a distributed auction mechanism leveraging a dual-ring communication topology, capable of handling six types of events: UAV failure, UAV addition, node cancel exploration, node urgent exploration, node re-exploration and node in-depth exploration. Through event-driven auctions and group-based bidding, the system maintains a load imbalance under 28% and achieves effective rebalancing even under scenarios with over 50% UAV loss. These results validate the robustness and adaptability of the dual-ring dynamic scheduler in real-time collaborative coverage missions. The proposed method demonstrates significant potential in dynamic, large-scale UAV applications.