By connecting two well-known-in-literature simulation suites (FL-AIR for
CONTROL and NS-3 for NETWORKING), we are able to perform real-time
accurate simulations of the wireless communication among fleets of
UAVs, and analyze the impact of the radio propagation phenomena and
packet level simulation on the fleet mobility algorithms.
The current merging of networking and control research fields within the
scope of robotic applications is creating fascinating research and
However, the tools for a proper and easy management of experiments still
Although different solutions have been proposed to simulate and emulate
control systems and, more specifically, fleets of Unmanned Aerial
Vehicles (UAV), still they do not include an efficient and detailed
network-side simulation, which is usually available only on dedicated
On the other hand, current advancements in network simulations suites
often do not present 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….
What is it?
We fill such gap in the literature by proposing a novel simulation
framework for networked control system, called CommUnicationS-Control
distribUted Simulator (CUSCUS). Differently from the state of the art,
CUSCUS allows simulating both the UAV networking and flight control,
via the integration of two existing tools: the Framework Libre AIR(FL-AIR) simulator and the
mainstream network simulator NS-3 .
What does it do?
Using FL-AIR, a real-time and fine-grained simulation of the
micro-mobility of each UAV can be achieved, including:
the modeling of virtual sensors/actuators,
the modeling of the aerial networking a packet-level
the modeling of formation control algorithms
the modeling of flight control algorithms
the PID regulations and the drone stability.
Why the term "Distributed"?
Levaraging the FLAIR part, it is possible to create UAV applications and
test them on a simulated control environment before the actual
deployment, since the same code can also be plugged in real drones.
In CUSCUS (and FLAIR), each virtual drone application is responsible to
simulate its flight model and control and then socket-out the data to a
rendering/control room engine.
This means that it is always possible to connect a real drone to the
engine and run it alongside its virtual fellows.
To make the simulation even more realistic and make a step towards the
usage of fleets of UAVs in Smart city scenarios, we just finished
implementating a Scenario Module in both FL-AIR and NS-3.
Through the Scenario Module, it is possible to model realistic 3D
environments, importing the scenario maps directly from OpenStreetMaps
and taking into account the location of buildings and the street
How does it work?
We have some papers in review, so it is better to keep that for
ourselves (for the moment, then it will be public domain, maybe…).
If you think that "bells and whistles" are too mainstream, you can
try your luck with a set of script that we ourselves leveraged to
perform the scientific work. Unfortunately (sic.) here are some of their features:
Works only under Linux
Ubuntu 14.04…If you manage to make the scripts work on another distro please let us know