Cognitive Agent Mobility for Aerial Sensor Networks

For efficient sensor coverage of large industrial and incident areas, fast and flexible strategies for collecting sensor data through an autonomous, wirelessly connected swarm of (Micro) Unmanned Aerial Vehicles (MUAVs) are still an emerging challenge. Deploying multiple MUAVs which stably carry sensing equipment in hostile environments yields cost efficiency and reducing the risk to human life. The use of an aerial ad hoc sensor network based on MUAV agents promises more timely and accurate information by fusing measurements from different types of sensors. In this paper, we examine agent-based mobility algorithms that target high spatial coverage distribution, high total coverage, and high-quality communication links. For these key figures, the performance of the different novel mobility algorithms is evaluated. We particularly focus on channel aware mobility and on self-organizing mesh topologies of MUAV-based sensor swarms with respect to communication constraints.

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