Alessandro Scarciglia
Implementation of Pure and Hybrid Visual Odometries on electric self-driving all-terrain vehicles.
Rel. Marcello Chiaberge. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2020
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Abstract
The design of a fully autonomous mobile platform is tightly related to the development of a reliable navigation system. In such context, the problem of the self-localisation covers one of the most important challenges. Nowadays both autonomous and non-autonomous vehicles mainly rely on GPS when dealing with pose estimation. As a drawback, the GPS system is likely to return a non-informative estimate for short-range displacements (i.e. indoor mobile robots operations), as well as in some places the signal can be either unreliable or totally absent. For the reasons mentioned above, a good self-contained localisation system needs to be integrated, in order to fulfill the localisation issue in a wider range of environments.
The purpose of this research work is to develop a real-time application in order to get a vision-based pose estimate of a Polaris electric all-terrain vehicle equipped with an omnidirectional catadioptric camera
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