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Laser scanner based heading angle and distance estimation
dc.contributor.author | Cáceres Hernández, Danilo | |
dc.contributor.author | Filonenko, Alexander | |
dc.contributor.author | Seo, Dongwook | |
dc.contributor.author | Hyun Jo, Kang | |
dc.date.accessioned | 2018-06-29T21:54:33Z | |
dc.date.accessioned | 2018-06-29T21:54:33Z | |
dc.date.available | 2018-06-29T21:54:33Z | |
dc.date.available | 2018-06-29T21:54:33Z | |
dc.date.issued | 03/17/2013 | |
dc.date.issued | 03/17/2013 | |
dc.identifier | https://ieeexplore.ieee.org/abstract/document/7125345/ | |
dc.identifier.uri | http://ridda2.utp.ac.pa/handle/123456789/5094 | |
dc.identifier.uri | http://ridda2.utp.ac.pa/handle/123456789/5094 | |
dc.description | Towards 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.abstract | Towards 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.format | application/pdf | |
dc.format | text/html | |
dc.language | eng | |
dc.rights | info:eu-repo/semantics/embargoedAccess | |
dc.subject | Roads | en_US |
dc.subject | Laser beams | en_US |
dc.subject | Vehicles | en_US |
dc.subject | Navigation | en_US |
dc.subject | Surface emitting lasers | en_US |
dc.subject | Measurement by laser beam | en_US |
dc.subject | Roads | |
dc.subject | Laser beams | |
dc.subject | Vehicles | |
dc.subject | Navigation | |
dc.subject | Surface emitting lasers | |
dc.subject | Measurement by laser beam | |
dc.title | Laser scanner based heading angle and distance estimation | en_US |
dc.type | info:eu-repo/semantics/article | |
dc.type | info:eu-repo/semantics/publishedVersion |
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