以多异构无人机执行侦查、打击、评估任务为背景,开展了协同任务规划问题建模、一体化求解算法设计。采用分布式规划框架及图论思想对问题进行建模,且将无人机避碰、燃油、任务执行次序作为约束条件,并充分考虑任务分配与路径规划存在的强耦合特性,采用禁忌/遗传算法,设计包含任务序列和路径位姿点的基因编码,将问题进行一体化求解。结果表明:算法能够适用于动态任务场景,且能够较为快速地解决任务空间较为复杂的规划问题。 With multi-heterogeneous UAV implementation of the investigation, combat, assessment tasks as the background, carried out collaborative mission planning problem modeling, integrated solution algorithm design. Using distributed planning framework and graph theory, the problem is modeled, and the order of avoiding collision avoidance, fuel and task execution is taken as the constraint, and the strong coupling between task assignment and path planning is considered. Taboo / heredity The algorithm designs the gene coding which contains the task sequence and path position and attitude, and solves the problem integrally. The results show that the algorithm can be applied to dynamic task scenarios and can solve more complicated planning problems in task space more quickly.