Skip to Main Content
Ad-hoc aerial sensor networks leveraging MUAVs (Micro Unmanned Aerial Vehicles) are ideally suited to cost-efficiently explore unknown or hostile environments for example in case of incidents producing harmful gases or radiation. In this manuscript we present results on the investigations of communication-aware steering algorithms for cooperative MUAV swarms. The mission objective is to achieve a maximum spatial exploration efficiency with the simultaneous ability to self-optimize the communication links by exploiting controlled mobility. While our previous work has mainly considered the performance of the Air-to-Air mesh network, in this paper we focus on the Air-to-Ground-link connectivity control. To achieve appropriate communication links to a central sensor data sink even while exploring larger search areas, an agent-based role management strategy is used to provide suitable multi-hop connectivity. The novel algorithms are investigated for static as well as dynamically changing environments. Key results include a detailed realistic aerial channel characterization and network dimensioning analysis considering numbers of MUAVs and density of ground stations vs. exploration speed and sensor data latency.