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Simultaneous Localization and Mapping algorithms benchmark for Autonomous Driving

Stefano Vitrani

Simultaneous Localization and Mapping algorithms benchmark for Autonomous Driving.

Rel. Andrea Tonoli. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2024

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Abstract:

In the context of Autonomous Driving (AD), Simultaneous Localization and Mapping (SLAM) algorithms are of fundamental importance in enabling vehicles to navigate and interact with the surrounding environment, with no input from a human driver. These algorithms are used to construct a map of the surroundings while estimating, at the same time, the position and trajectory of the vehicle inside of it. This thesis, developed as a collaboration between Politecnico di Torino and Italdesign Giugiaro, aims to adapt some of the best open-source SLAM algorithm to an internal AD project of the company, the autonomous vehicle prototype called Techdemo. The focus of this work is to integrate the algorithms in the software of the Techdemo to generate a map of the surroundings and conduct benchmark testing finalised at selecting the best one for the application.

Relators: Andrea Tonoli
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 75
Subjects:
Corso di laurea: Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo)
Classe di laurea: New organization > Master science > LM-33 - MECHANICAL ENGINEERING
Aziende collaboratrici: ITALDESIGN GIUGIARO SPA
URI: http://webthesis.biblio.polito.it/id/eprint/30491
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