异构资源类型下多无人机任务分配

针对多无人机在执行侦察、打击任务的过程中携带任务资源的异构性,以及任务对于异构资源的要求,设计了一种改进的基于共识的捆绑算法(consensus-based bundle algorithm, CBBA)。考虑任务价值、任务执行时间窗以及航程代价等条件建立了多无人机对地目标侦察、打击任务分配模型。利用K-medoids聚类分析方法对多无人机进行基于距离和携带资源平衡的聚类,以解决多无人机对于异构资源类型的要求。对打击任务进行子任务生成,并利用改进后的CBBA求解所建立的任务分配模型,通过对比仿真实验验证了算法的可行性和有效性。

Task allocation of multiple UAVs under heterogeneous resource types

An improved CBBA(consensus-based bundle algorithm) was proposed to solve the heterogeneity of task resources carried by multi-UAVs during reconnaissance and strike missions, and the requirements of tasks for heterogeneous resources. Considering the mission value, mission execution time window and range cost, a task allocation model of multi-UAV reconnaissance and attack on ground targets was established.K-medoids clustering analysis method was used to cluster multi-UAVs based on distance and the balance of carrying resources to solve the requirements of multi-UAVs for heterogeneous resource types. The attack task was generated into subtasks, and the improved CBBA was used to solve the established task allocation model. The feasibility and effectiveness of the algorithm are verified by comparison simulation experiments.