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dc.contributor.authorCáceres Hernández, Danilo
dc.contributor.authorFilonenko, Alexander
dc.contributor.authorSeo, Dongwook
dc.contributor.authorHyun Jo, Kang
dc.date.accessioned2018-06-29T21:54:33Z
dc.date.accessioned2018-06-29T21:54:33Z
dc.date.available2018-06-29T21:54:33Z
dc.date.available2018-06-29T21:54:33Z
dc.date.issued03/17/2013
dc.date.issued03/17/2013
dc.identifierhttps://ieeexplore.ieee.org/abstract/document/7125345/
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/5094
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/5094
dc.descriptionTowards autonomous vehicle navigation the problem of guidance is a major difficulty faced by fully autonomous vehicle. This paper proposes a new method to estimate the heading angle for safe autonomous navigation purpose. The authors focus on unconventional methods of identifying lane markings on a road surface through Laser Measurement System (LMS). This was achieved by taking advantage of the reflection of the laser beam. This method was executed in three steps. Firstly to detect lane markings we employed the Density-based spatial clustering of applications with noise (DBSCAN) method. Secondly, in order to determine the surface course a distance clustering analysis was implemented. Lastly, the steering angle as well as the lateral distance between the heading and the goal point was estimated. Preliminary results were performed and tested on a group of consecutive fames to prove its effectiveness.en_US
dc.description.abstractTowards autonomous vehicle navigation the problem of guidance is a major difficulty faced by fully autonomous vehicle. This paper proposes a new method to estimate the heading angle for safe autonomous navigation purpose. The authors focus on unconventional methods of identifying lane markings on a road surface through Laser Measurement System (LMS). This was achieved by taking advantage of the reflection of the laser beam. This method was executed in three steps. Firstly to detect lane markings we employed the Density-based spatial clustering of applications with noise (DBSCAN) method. Secondly, in order to determine the surface course a distance clustering analysis was implemented. Lastly, the steering angle as well as the lateral distance between the heading and the goal point was estimated. Preliminary results were performed and tested on a group of consecutive fames to prove its effectiveness.en_US
dc.formatapplication/pdf
dc.formattext/html
dc.languageeng
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectRoadsen_US
dc.subjectLaser beamsen_US
dc.subjectVehiclesen_US
dc.subjectNavigationen_US
dc.subjectSurface emitting lasersen_US
dc.subjectMeasurement by laser beamen_US
dc.subjectRoads
dc.subjectLaser beams
dc.subjectVehicles
dc.subjectNavigation
dc.subjectSurface emitting lasers
dc.subjectMeasurement by laser beam
dc.titleLaser scanner based heading angle and distance estimationen_US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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