一种未知动态环境下异构无人机集群分布式联盟形成方法

Aiming at the problem of distributed coalition formation of heterogeneous UAV swarm in unknown dynamic environment, we first construct the coalition task automata of heterogeneous UAV swarm to realize the autonomous task coordination of heterogeneous UAV swarm. On this basis, a distributed coalition formation algorithm based on Monte-Carlo tree search is proposed, which increments the distributed optimization of coalition structure through a two-stage Monte-Carlo tree search. The algorithm can be implemented in a distributed framework and can terminate at any time to return the current optimal solution. Finally, the simulation results show that the proposed algorithm can effectively deal with the problem of distributed coalition formation of heterogeneous UAV swarm in an unknown and dynamic environment, and can maintain better performance in the large-scale coalition formation problem.