Rough terrain profiling using digital image correlation
dc.contributor.author | Botha, Theunis R. | |
dc.contributor.author | Els, Pieter Schalk | |
dc.contributor.email | schalk.els@up.ac.za | en_ZA |
dc.date.accessioned | 2016-03-15T08:05:00Z | |
dc.date.issued | 2015-06 | |
dc.description.abstract | Road profiling is an important aspect of vehicle dynamics simulations especially over rough terrains. The accurate measurement of rough terrains allows for more accurate multi body simulations. Three dimensional road profiles are usually performed by utilising a line scan sensor which measures several points lateral to the road. The sensors range from simple road following wheels to LiDAR sensors. The obtained line scans are longitudinally stitched together using the orientation and position of the sensor to obtain a full three dimensional road profile. The sensor’s position and orientation therefore needs to be accurately determined in order to combine the line scans to create an accurate representation of the terrain. The sensor’s position and orientation is normally measured using an expensive inertial measurement unit or Inertial Navigation System (INS) with high sensitivity, low noise and low drift. This paper proposes a road profiling technique which utilises stereography, based on two inexpensive digital cameras, to obtain three-dimensional measurements of the road. The system negates the use of an expensive INS system to determine orientation and position. The data sets also require subsampling which can be computationally expensive. A simple subsampling routine is presented which takes advantage of the structure of the data sets to significantly speed up the process. | en_ZA |
dc.description.embargo | 2016-06-30 | |
dc.description.librarian | hb2015 | en_ZA |
dc.description.librarian | mi2025 | en |
dc.description.sdg | SDG-09: Industry, innovation and infrastructure | en |
dc.description.sdg | SDG-11: Sustainable cities and communities | en |
dc.description.sdg | SDG-15: Life on land | en |
dc.description.sponsorship | National Research Foundation (DAAD-NRF). | en_ZA |
dc.description.uri | http://www.elsevier.com/locate/jterra | en_ZA |
dc.identifier.citation | Botha, TR & Els, PS 2015, 'Rough terrain profiling using digital image correlation', Journal of Terramechanics, vol. 59, pp. 1-17. | en_ZA |
dc.identifier.issn | 0022-4898 (print) | |
dc.identifier.issn | 1879-1204 (online) | |
dc.identifier.other | 10.1016/j.jterra.2015.02.002 | |
dc.identifier.uri | http://hdl.handle.net/2263/51831 | |
dc.language.iso | en | en_ZA |
dc.publisher | Elsevier | en_ZA |
dc.rights | © 2015 ISTVS. Published by Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Journal of Terramechanics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Terramechanics, vol. 59, pp. 1-17, 2015. doi : 10.1016/j.jterra.2015.02.002. | en_ZA |
dc.subject | Rough | en_ZA |
dc.subject | Road profiling | en_ZA |
dc.subject | Profilometer | en_ZA |
dc.subject | Digital image correlation | en_ZA |
dc.subject | Point cloud interpolation | en_ZA |
dc.subject | Camera stereovision | en_ZA |
dc.subject.other | Engineering, built environment and information technology articles SDG-09 | |
dc.subject.other | SDG-09: Industry, innovation and infrastructure | |
dc.subject.other | Engineering, built environment and information technology articles SDG-11 | |
dc.subject.other | SDG-11: Sustainable cities and communities | |
dc.subject.other | Engineering, built environment and information technology articles SDG-15 | |
dc.subject.other | SDG-15: Life on land | |
dc.title | Rough terrain profiling using digital image correlation | en_ZA |
dc.type | Postprint Article | en_ZA |