  With the rapid advancement of UAV technology, the problem of UAV coalition
formation has become a hotspot. Therefore, designing task-driven multi-UAV
coalition formation mechanism has become a challenging problem. However,
existing coalition formation mechanisms suffer from low relevance between UAVs
and task requirements, resulting in overall low coalition utility and unstable
coalition structures. To address these problems, this paper proposed a novel
multi-UAV coalition network collaborative task completion model, considering
both coalition work capacity and task-requirement relationships. This model
stimulated the formation of coalitions that match task requirements by using a
revenue function based on the coalition's revenue threshold. Subsequently, an
algorithm for coalition formation based on marginal utility was proposed.
Specifically, the algorithm utilized Shapley value to achieve fair utility
distribution within the coalition, evaluated coalition values based on marginal
utility preference order, and achieved stable coalition partition through a
limited number of iterations. Additionally, we theoretically proved that this
algorithm has Nash equilibrium solution. Finally, experimental results
demonstrated that the proposed algorithm, compared to currently classical
algorithms, not only forms more stable coalitions but also further enhances the
overall utility of coalitions effectively.
