CAJ | 학술논문

针对大规模任务分配问题，为了提高任务分配的效率和合理性，提出了基于任务依赖关系和ISODA-TA算法相结合的任务分组方法。在任务分组基础上，从无人机负载均衡的角度出发，提出了基于资源福利的任务组级粗粒度任务分配方法，结合粒子群算法提出了任务组内的细粒度任务分配算法。通过实验仿真验证所提方法有效，且性能和灵活性较普通任务分配算法有较大的优势。
침대대규모임무분배문제，위료제고임무분배적효솔화합이성，제출료기우임무의뢰관계화ISODA-TA산법상결합적임무분조방법。재임무분조기출상，종무인궤부재균형적각도출발，제출료기우자원복리적임무조급조립도임무분배방법，결합입자군산법제출료임무조내적세립도임무분배산법。통과실험방진험증소제방법유효，차성능화령활성교보통임무분배산법유교대적우세。
Multi-UAV ( unmanned aerial vehicle) task assignment is a key issue in the field of unmanned combat command and control. To improve the efficiency and rationality of algorithm for large-scale task assignment, a grouping method was first presented based on combination of task constraints and ISODATA( iterative self-organizing data analysis technique) algorithm. On the basis of the task grouping, a coarse-grained task assignment method was proposed based on UAV group resource welfare from the perspective of load balance. Combined with PSO( particle swarm optimization) a fine-grained task assignment algorithm was given. The simulation proves better effective per-formance and more flexibility than the ordinary task allocation algorithm.