Abstract

This article describes how swarm intelligence can be applied to an array of autonomous unmanned aerial vehicles (UAVs) for strategic deployment. In emergency or disaster-stricken areas, telecommunications and geospatial surveillance are strictly critical for situational control. Base stations may fail to work due to natural disasters. To be rapidly deployed, lightweight drones with multirotors that provide stability are used as mobile stations. An autonomous learning approach, “self-organizing maps (SOMs),” which can automatically and adaptively coordinate a large array of autonomous drones—self-organizing UAV array—based on requests from end users (EUs) is embedded inside the array. The size and the topology of a UAV array can be dynamically changed in response to various terrains and relocation of EUs. Moreover, with swarm intelligence, the UAV array is capable of reconfiguring its planar topology into a hierarchical one. Such a hierarchical topology divides the entire UAV array into subarrays and creates isolated heterogeneous networks. Thus, the UAV array can cope with diverse situations across geographical barriers by forming a flying ad hoc network.

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