A Distributed Collaborative Allocation Method of Reconnaissance and Strike Tasks for Heterogeneous UAVs

Unmanned aerial vehicles (UAVs) are becoming more and widely used in battlefield reconnaissance target strikes because of their high cost-effectiveness, but task planning for large-scale UAV swarms is a problem that needs to be solved. To solve the high-risk caused by incomplete information combat area potential coordination between targets when heterogeneous swarm performs strike missions, this paper proposes distributed task-allocation algorithm. The method prioritizes tasks evaluating swarm’s capability superiority reduce search space, uses time mechanism deterrent maneuver strategy risk negotiation allocate coordinated tasks. simulation results under framework verify effectiveness mechanism, comparative experiments different strategies show can effectively mission unknown. comparison with centralized global optimization algorithm verifies efficiency proposed applied swarms. Since architecture avoids dependence on highly reliable network central node, it further improve reliability scalability swarm, make applicable complex environments.