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dc.contributor.advisorStahl, Annette
dc.contributor.authorGustavsen, Lars
dc.date.accessioned2019-09-11T11:41:27Z
dc.date.created2018-08-19
dc.date.issued2018
dc.identifierntnudaim:18609
dc.identifier.urihttp://hdl.handle.net/11250/2616057
dc.description.abstractThis thesis describes the development of a perception system for an autonomous racecar on behalf of the Driverless team at Revolve NTNU. My contribution has an extra focus on the issue of localization and mapping. The motivation for this thesis was to develop a system that met the goals set by the organization for the first year in the Driverless class, which was to complete all race events successfully. A simultaneous localization and mapping (SLAM) system has been implemented using an incremental smoothing and mapping backend. Through adding odometry measurements and landmarks to a factor graph, the system produces an accurate position and orientation of the vehicle, as well as the cones delimiting the racetrack. With this localization information we are able to plan a route around the racetrack which we then can follow.en
dc.languageeng
dc.publisherNTNU
dc.subjectKybernetikk og robotikk, Innvevde datasystemeren
dc.titleDeveloping a mapping system for an autonomous Formula Student racecaren
dc.typeMaster thesisen
dc.source.pagenumber75
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi og elektroteknikk,Institutt for teknisk kybernetikknb_NO
dc.date.embargoenddate10000-01-01


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