Riccardo Catania
Enhancing UAV Autonomous Indoor Flight with Visual Odometry Techniques.
Rel. Alessandro Rizzo, Stefano Primatesta. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2023
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Abstract
In the rapidly evolving industrial landscape, Unmanned Aerial Vehicles (UAVs) have emerged as a pivotal component in enhancing operational efficiency and safety. These autonomous systems are particularly crucial in environments where direct human intervention is challenging or risky. The ultimate goal of this project is to assist human operators in specific missions by collecting and processing data. The drone should be able to provide stable flight in GNSS (Global Navigation Satellite System) denied environments exploiting the visual odometry algorithms and specific sensors. This thesis is a part of the FIXIT project, an initiative by the Competence Industry of Manufacturing 4.0 in Turin, Italy.
The FIXIT project aims to establish a cooperative system between a UAV and an Autonomous Ground Vehicle (AGV), where the UAV can perform autonomous flights in industrial environments and dock on a moving rover
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