Swarming algorithms to achieve goal based missions

使用蜂群执行任务并不是一个新话题，一些公司正在考虑使用大量无人机来完成这些任务。这种蜂群通常是使用诸如地面站或载人飞行器/飞行器等中央系统来控制的，由于指挥结构的原因，这不被认为是利用真正的蜂群能力。紧急群体行为的优点是克服了操作员指挥和控制人力的过度使用，并变得有弹性，而不是依赖于分层的单点故障控制节点。拟议的研究是为了确定决定智力水平和单位间沟通的特征，这些特征是建立和影响整个蜂群中不同的紧急行为所必需的。这项研究将确定如何从一个参数化的简单部署算法中得出不同的紧急行为。

Using swarms to conduct missions is not a new topic and a number of companies are looking at the application of large numbers of drones to achieve these missions. Such swarms are typically controlled using a centralised system such as a ground station or manned aircraft/ vehicle, and this is not considered as exploiting true swarm capabilities due to the command structure. The advantage of emergent swarm behaviours is to overcome the excessive operator Command and Control manpower utilisation, and to become resilient, and not reliant upon hierarchical, single point of failure control nodes. The proposed research is to identify the characteristics which determine the level of intelligence, and inter unit communications, necessary to establish and affect different emergent behaviours from the overall swarm. The research will identify how different emergent behaviours could be derived from a parametrised simple deployed algorithm.