Irisa Ibrahimi
Integrating Real-Time Object Detection with LiDAR Data for Enhanced Robotic Autonomous Navigation.
Rel. Marina Indri, Gianluca Prato. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024
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Abstract
The adoption of autonomous mobile robots in complex environments, such as warehouses, factories, offices, airports, and metropolitan areas, has been steadily increasing in recent years due to technology advancements in fields such as artificial intelligence, edge low-power computing platforms, and sensor systems. The main focus of this thesis was the integration of YOLO (You Only Look Once), a neural network for object identification, within the navigation system already installed onboard a robotic platform to improve its detection capabilities and handling of dynamic obstacles on the road, such as cars and other vehicles. This thesis, developed within the LINKS Foundation in Turin, originated as an extension of an autonomous navigation project initially geared toward indoor mail delivery by TurtleBot robots.
To address the challenges posed by outdoor navigation and in the context of last-mile deliveries, the project was subsequently oriented toward the use of Agilex's Scout 2.0, a mobile robot designed to operate in outdoor contexts
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