The CUSCUS simulator for distributed networked control systems: Architecture and use-cases

The current merging of networking and control research fields within the scope of robotic applications is creating fascinating research and development opportunities. However, the tools for a proper and easy management of experiments still lag behind. Although different solutions have been proposed to simulate and emulate control systems and, more specifically, fleets of Unmanned Aerial Vehicles (UAVs), still they do not include an efficient and detailed network-side simulation, which is usually available only on dedicated software. On the other hand, current advancements in network simulations suites often do not include the possibility to include an accurate description of controlled systems. In the middle 2010s, integrated solutions of networking and control for fleets of UAVs are still lacking. In this paper, we fill such gap by presenting a simulation architecture for networked control systems which is based on two well-known solutions in both the fields of networking simulation (the NS-3 tool) and UAV control simulation (the FL-AIR tool). Three main research contributions are provided: (i) first, we show how the existing tools can be integrated on a closed-loop architecture, so that the network propagation model (NS-3 side) is influenced by the drone mobility and by the 3D scenario map (FL-AIR side); (ii) second, we implement a novel module, which allows modeling realistic 3D environments by importing city-wide characteristics by the popular OpenStreetMap service; (iii) third, we demonstrate the modeling capabilities of the CUSCUS framework on two realistic use-cases, corresponding to well-known application scenarios of UAVs, i.e. dynamic formation control and static coverage of a target area.