Researchers Develop Automated Flight Control System For Drone Swarms


An automated flight control algorithm has been developed to control drone swarms from a single ground station.

Drone swarms refer to multiple drones flying similar to the flock of birds. These drones can be controlled by a single base station or can be self-controlled based on automation algorithms built during their development. For such an organized army of drones, connectivity is important. Here, 5G networks and computer security systems will play a critical role.

Researchers from the Universidad Carlos III de Madrid have developed an automated flight control system for drone swarms. “The project’s main objective is to integrate a certain degree of automation, so that an operator can control a small fleet of up to 10 drones from a single ground station,” says Luis E. Moreno, LABYRINTH’s coordinator and researcher at the UC3M’s Robotics Lab. “The idea is that the operator indicates the mission to be undertaken (for example, monitoring traffic in a particular area) and the system automatically converts this mission into a set of routes that each drone has to follow, automatically calculating alternative routes when necessary,” he explains.

The researchers have developed a planning algorithm for planning routes and preventing collisions for drone swarms in three-dimensional environments. The algorithm is responsible for calculating optimal, fluid routes for a set of drones. They implemented different measures (flights at different altitudes, distance control, etc.) to obtain a strategy for avoiding possible collisions. The work was published in the Sensors journal.

“Air controllers use ATM (Air Traffic Management) to safely manage the traffic of commercial aircraft. Similarly, developing an Unmanned Traffic Management (UTM) system that allows drones to share airspace with other drones and aircraft is imperative,” explains Francisco Valera, another scientist taking part in this project and a member of NETCOM (Networks and Communications Services) at the UC3M.

For more information, visit the LABYRINTH project page http://labyrinth2020.eu/.


 





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