Task allocation enables heterogeneous agents to execute heterogeneous tasks in the domain of unmanned aerial vehicles, while responding to dynamic changes in the environment and available resources to complete complex, multi-objective missions, leading to swarm intelligence. We propose a bio-inspired approach using digital pheromones to perform scalable task allocation when the number of agents, tasks, and the diameter of the communications graph increase. The resulting emergent behaviour also enables idle agents in the swarm to provide periodic or continuous connectivity between disconnected parts of the swarm. We validate our results through simulation and demonstrate the feasibility of our approach by applying it to the 3D coverage and patrol problem.

任务分配使异构代理能够在无人机领域执行异构任务，同时响应环境和可用资源的动态变化来完成复杂的多目标任务，从而产生群体智能。我们提出了一种仿生方法，当代理、任务的数量和通信图的直径增加时，使用数字信息素来执行可扩展的任务分配。由此产生的紧急行为还使群中的空闲代理能够在群中断开连接的部分之间提供定期或连续的连接。我们通过模拟验证我们的结果，并通过将其应用于 3D 覆盖和巡逻问题来证明我们的方法的可行性。