DEVIN

Over the past 15 years, the popularity and accessibility of unmanned aerial vehicles has seriously increased. The number of incidents involving drones flying over or landing on critical infrastructures around the world (the White House, the Japanese Prime Minister's office, the Golden Gate Bridge, nuclear sites in France, prison facilities, etc.) is increasing. Although regulations are strict and require a number of rules depending on the class of the vehicle, these devices can be easily disconnected on commercial aircrafts and can be omitted on clandestinely manufactured aircrafts. In the DEVIN project, we are interested in the detection, localization, tracking and encirclement of an enemy drone by a UAVs swarm. In order to address the scientific challenges identified and stated above, we assume that the swarm evolves in an unknown and potentially dynamic environment. In addition to their Inertial Measurement Unit, they will be equipped with a spherical event camera. The latter will allow each drone in the swarm to detect and locate a potential enemy and to ensure its autonomous pursuit. It will also serve as a means of communication between the drones in the swarm using single-pattern light flashes. The control of the swarm will be ensured by decentralized controllers based on reinforcement learning easily transferable to the real world and having stability properties. This project will allow to obtain an easily transportable solution by using as a means of detection, localization and tracking, a swarm of UAVs each embarked with mobile and small size sensors. DEVIN is positioned as an indispensable complementary approach in the short term to the solutions developed to date, whose main drawback is that they cannot ensure the security of mobile sites (demonstrations, processions, etc.).