Rapid close surrounding evaluation for autonomous commercial vehicles

dc.contributor.authorBagchi, Shamit
dc.contributor.authorSoultani, Evangelia
dc.contributor.departmentChalmers tekniska högskola / Institutionen för tillämpad mekaniksv
dc.contributor.departmentChalmers University of Technology / Department of Applied Mechanicsen
dc.date.accessioned2019-07-03T14:16:11Z
dc.date.available2019-07-03T14:16:11Z
dc.date.issued2016
dc.description.abstractA framework has been developed for local, relative navigation of an autonomous commercial vehicle in confined areas. This enables a vehicle to navigate based only on its immediate surroundings, with the vehicle as the reference. The framework uses a simulator, to simulate the environment of a mine, and a vehicle model. The latter is equipped with 2D LIDAR sensors which allow it to interpret its close surroundings. Based on this information, a navigation algorithm is selected which performs the path planning and moves the vehicle. Four such algorithms have been developed in order to handle two distinct scenarios: navigation in a corridor and navigation at an intersection. The algorithms have been evaluated for safety and accuracy and perform consistently well. The overall root mean square deviation from a reference path is less than 25% of a chosen collision threshold. Throughout the evaluation, a safe distance from all the walls was maintained. In addition, the path generation algorithms were highly efficient with an average execution time of under 2 milliseconds. This work opens up the possibilities for algorithms which can handle additional navigation scenarios and can learn and adapt to its environment.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/238916
dc.language.isoeng
dc.relation.ispartofseriesDiploma work - Department of Applied Mechanics, Chalmers University of Technology, Göteborg, Sweden : 2016:40
dc.setspec.uppsokTechnology
dc.subjectFarkostteknik
dc.subjectTransport
dc.subjectVehicle Engineering
dc.subjectTransport
dc.titleRapid close surrounding evaluation for autonomous commercial vehicles
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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