Unmanned aerial vehicles (UAVs) have significant prospects in a plethora of public and civic spheres. Recently, UAVs have focused primarily on applications where human presence is either impossible or hazardous. A swarm of small UAVs can cooperatively complete operations more proficiently and economically than a single large UAV. However, many issues must be resolved before stable and reliable multi-UAV networks can be realized. Task assignment in fleets of UAVs is concerned with cooperative decision-making and control. UAVs possess various functional abilities and kinematic constraints while carrying limited resources onboard. UAVs are nominated to execute multiple sequential tasks supportively on numerous ground targets. The prime objective of task assignment is to minimalize the task accomplishment time and UAV energy consumption. To date, several task assignment algorithms have been designed for UAV networks, and they are comprehensively surveyed in this paper in terms of their main ideas, operational features, advantages, and limitations. These task assignment algorithms are then compared in terms of their significant characteristics and performance factors. To the best of the authors' knowledge, no survey on task assignment techniques for different UAV missions currently exists in the literature. We also discuss open issues and challenges and then suggest projections for task assignment algorithms concerning possible future directions.

无人驾驶飞行器 (UAV) 在众多公共和公民领域具有重要的前景。最近，无人机主要专注于人类不可能或危险的应用。与单个大型无人机相比，一群小型无人机可以更熟练、更经济地协同完成作业。但是，要实现稳定可靠的多无人机网络，还需要解决很多问题。无人机机队的任务分配与协作决策和控制有关。无人机在携带有限资源的同时具有各种功能能力和运动学限制。无人机被指定在众多地面目标上支持执行多个顺序任务。任务分配的主要目标是最小化任务完成时间和无人机能量消耗。迄今为止，已经为无人机网络设计了几种任务分配算法，本文对它们的主要思想、操作特性、优势和局限性进行了全面的研究。然后根据它们的重要特征和性能因素比较这些任务分配算法。据作者所知，目前文献中没有针对不同无人机任务的任务分配技术的调查。我们还讨论了未解决的问题和挑战，然后就可能的未来方向提出任务分配算法的预测。然后根据它们的重要特征和性能因素比较这些任务分配算法。据作者所知，目前文献中没有针对不同无人机任务的任务分配技术的调查。我们还讨论了未解决的问题和挑战，然后就可能的未来方向提出任务分配算法的预测。然后根据它们的重要特征和性能因素比较这些任务分配算法。据作者所知，目前文献中没有针对不同无人机任务的任务分配技术的调查。我们还讨论了未解决的问题和挑战，然后就可能的未来方向提出任务分配算法的预测。