Designed and developed in collaboration with seven Italian universities, the Leonardo Drone Contest was created to promote the development of artificial intelligence applied to unmanned systems and aims to encourage the creation of an innovation ecosystem that involves and brings together the capabilities of large companies, universities, SMEs and Italian spin-offs and start-ups.
The competition aims to develop advanced technological solutions in the field of autonomous mobility, which can be applied to complex and real scenarios, such as monitoring areas affected by natural disasters or surveillance of high-risk and difficult-to-access areas.
The Drone Contest was launched in 2020, and involved, in the first three editions, six Italian universities: Politecnico of Turin, Politecnico of Milan, University of Rome Tor Vergata, Scuola Superiore Sant'Anna of Pisa, University of Naples Federico II, Alma Mater Studiorum - University of Bologna. The Politecnico of Bari has joined them since the fourth edition.
During the sixth edition, which took place on 1-2 October 2025 as side event of Italian Tech Week, participants tested their collaborative systems, consisting of drones and ground robots, in a scenario simulating an urban environment. The robots were called upon to perform specific tasks aimed at supporting and accelerating the human decision-making process, reducing intervention times.
First place went to the University of Rome Tor Vergata, followed by the Polytechnic University of Milan and the University of Naples Federico II.
Participants in the 2025 edition experimented with autonomous robotic platforms, both aerial (Unmanned Aerial Vehicles - UAVs) and terrestrial (Unmanned Ground Vehicles - UGVs), capable of moving in unknown environments without a GNSS (Global Navigation Satellite System) signal, while providing information and maps to a ground control station. At the heart of the challenge was the development of innovative solutions for localisation, navigation and human-machine collaboration, based on artificial intelligence algorithms capable of processing the collected data in real time.
