Cooperative Dubins-Based Task Planning for Multiple UAVs in Complex Obstacle Environments

The cooperative planning of multiple unmanned aerial vehicles (multi-UAV) for multi-target missions has gained increasing attention in recent years. This problem comprises three interdependent subproblems: task allocation, path planning, and cooperative optimization Under multiple constraints, these three subproblems are inherently coupled, influencing the overall effectiveness of the cooperative mission. This paper presents an integrated approach to address these challenges. First, a fair and optimal task allocation strategy is proposed, leveraging a distributed auction mechanism and optimization modeling to achieve balanced task distribution among UAVs. Second, a pruning-bridging-backtracking Dubins path planning framework is developed to facilitate smooth trajectory generation in complex environments with obstacles. Finally, particle swarm optimization (PSO) combined with local search is employed for cooperative path optimization. Simulation results confirm that the proposed method effectively enhances safety and synchronization in multi-UAV multi-target synchronous planning within complex obstacle-laden environments.