Dynamic UAV Swarm Deployment for Non-Uniform Coverage

In many monitoring and mapping applications, high-resolution data are required only in certain areas while others can receive lower attention. To this end, unmanned aerial vehicles (UAVs) can adjust the flight altitude to increase the resolution only where needed, making non-uniform coverage strategies efficient both in time and energy expenditure. In a multi-UAV monitoring context, it is necessary to deploy UAVs to inspect in parallel those areas where a higher resolution is required. To address this problem, we propose a decentralised deployment strategy inspired by the collective behaviour of honeybees. This strategy dynamically assigns UAVs to different areas to be monitored, and suitably reassigns them to other areas when needed. We introduce an analytical macroscopic model of area monitoring from UAVs, and we propose a parameterisation that leads to an efficient allocation of UAVs to the areas to be monitored. We exploit abstract multi-agent simulations to study the dynamics of the deployment of UAVs to multiple areas, and we present results with simulations of a UAV swarm engaged in a weed monitoring and mapping task.