Swarming algorithms to achieve goal based missions

使用蜂群执行任务并不是一个新话题，许多公司正在考虑使用大量无人机来完成这些任务。这种蜂群通常使用中央系统控制，例如地面站或有人驾驶飞机/车辆，由于指挥结构，这不被认为是利用真正的蜂群能力。突发性群体行为的优点是克服了操作员指挥和控制人力的过度利用，并且变得有弹性，而不依赖于分层的单点故障控制节点。提出的研究是确定决定智力水平和单位间通信的特征，这些特征对于建立和影响整体群体的不同紧急行为是必要的。该研究将确定如何从参数化的简单部署算法中推导出不同的紧急行为。

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.