A Simple Self-Driving Robot

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dc.contributor.advisor Pelillo, Marcello it_IT
dc.contributor.author Signoretto, Marco <1994> it_IT
dc.date.accessioned 2018-06-13 it_IT
dc.date.accessioned 2018-12-03T06:20:47Z
dc.date.available 2018-12-03T06:20:47Z
dc.date.issued 2018-07-11 it_IT
dc.identifier.uri http://hdl.handle.net/10579/13246
dc.description.abstract In the last few years, autonomous driving has become a major topic in both car industry and academia. Many challenging problems remain to be solved, however, in order for autonomous cars to be on the market. In this thesis, I will describe the structure of a simple robotic system, called drAlver, which is able to navigate autonomously using computer vision algorithms. To reach this goal the problem has been decomposed into tasks. The first task is road line detection, two kinds of detector have been proposed. A basic line detector and an advanced line detector. The latter method shows more effective performances overcoming some limitations of the first one. The second one is the detection of cars, pedestrians, cyclists and traffic signs which is solved with a CNN, in particular using the YOLOv3 architecture. The above tasks are not solved on the robot's board due to its limited computational power. Instead, the robot is paired with a computer via a wireless connection. The thesis work is also related to the engineering and the development of the hardware and the software as well as the communication structure among computer and robot. The hardware is based on Raspberry Pi Model B which is able to control motors. To sense the surrounding environment, the robot captures images using a webcam positioned on its top. The communication between different modules is based on queues resulting in an asynchronous and parallelized system. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Marco Signoretto, 2018 it_IT
dc.title A Simple Self-Driving Robot it_IT
dc.title.alternative drAIver: A Simple Self-Driving Robot it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Informatica - computer science it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Scienze Ambientali, Informatica e Statistica it_IT
dc.description.academicyear 2017/2018, sessione estiva it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 850484 it_IT
dc.subject.miur INF/01 INFORMATICA it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend it_IT
dc.provenance.upload Marco Signoretto (850484@stud.unive.it), 2018-06-13 it_IT
dc.provenance.plagiarycheck Marcello Pelillo (pelillo@unive.it), 2018-07-02 it_IT


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