The Leonardo Drone Contest is an autonomous drone competition that aims at finding innovative solutions for drones operating in a Global Navigation Satellite System (GNSS) denied environment. At the end of a three years cycle of the competition, in this paper a review of the identified system and conclusions made by the DRAFT team from Politecnico di Torino is presented. The authors aim at introducing the final solutions to the challenge in terms of hardware components, algorithms and development process. The proposed approach has been widely tested and validated, and it ranked second in the competition. The well-consolidated procedure, resulting from many iterations in the development cycle, has contributed to further improvements during the three-year challenge and can be helpful for anyone who desires to approach the problem of autonomous drones employed in smart cities contexts.
Autonomous Drones in GNSS-Denied Environments: Results from the Leonardo Drone Contest / Godio, Simone; Marino, Francesco; Minervini, Alessandro; Primatesta, Stefano; Chiaberge, Marcello; Guglieri, Giorgio. - ELETTRONICO. - (2023). (Intervento presentato al convegno 10th International Workshop on Metrology for AeroSpace (MetroAeroSpace) tenutosi a Milan, Italy nel 19-21 June 2023) [10.1109/MetroAeroSpace57412.2023.10190003].
Autonomous Drones in GNSS-Denied Environments: Results from the Leonardo Drone Contest
Godio, Simone;Marino, Francesco;Minervini, Alessandro;Primatesta, Stefano;Chiaberge, Marcello;Guglieri, Giorgio
2023
Abstract
The Leonardo Drone Contest is an autonomous drone competition that aims at finding innovative solutions for drones operating in a Global Navigation Satellite System (GNSS) denied environment. At the end of a three years cycle of the competition, in this paper a review of the identified system and conclusions made by the DRAFT team from Politecnico di Torino is presented. The authors aim at introducing the final solutions to the challenge in terms of hardware components, algorithms and development process. The proposed approach has been widely tested and validated, and it ranked second in the competition. The well-consolidated procedure, resulting from many iterations in the development cycle, has contributed to further improvements during the three-year challenge and can be helpful for anyone who desires to approach the problem of autonomous drones employed in smart cities contexts.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2980661