Road curb and intersection detection using A 2D LMS

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dc.contributor.author Kodagoda, KRS
dc.contributor.author Wijesoma, WS
dc.contributor.author Balasuriya, AP
dc.date.accessioned 2010-07-13T08:50:33Z
dc.date.issued 2002
dc.identifier.citation IEEE International Conference on Intelligent Robots and Systems, 2002, 1 pp. 19 - 24
dc.identifier.other E1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/12669
dc.description.abstract In most urban roads, and similar environments such as in theme parks, campus sites, industrial estates, science parks and the like, the painted lane markings that exist may not be easily discernible by CCD cameras due to poor lighting, bad weather conditions, and inadequate maintenance. An important feature of roads in such environments is the existence of pavements or curbs on either side defining the road boundaries. These curbs, which are mostly parallel to the road, can be hardnessed to extract useful features of the road for implementing autonomous navigation or driver assistance systems. However, extraction of the curb or road edge feature using vision image data is a very formidable task as the curb is not conspicuous in the vision image. To extract the curb using vision data requires extensive image processing, heuristics and very favorable ambient lighting. In our approach, road curbs are extracted speedily using range data provided by a 2D Laser range Measurement System (LMS). Experimental results are presented to demonstrate the viability, and effectiveness, of the proposed methodology and its robustness to different road configurations including road intersections.
dc.relation.hasversion Accepted manuscript version en_US
dc.title Road curb and intersection detection using A 2D LMS
dc.type Conference Proceeding
dc.parent IEEE International Conference on Intelligent Robots and Systems
dc.journal.volume 1
dc.journal.number en_US
dc.publocation Switzerland en_US
dc.identifier.startpage 19 en_US
dc.identifier.endpage 24 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.conference IEEE/RSJ International Conference on Intelligent Robots and Systems
dc.for 091007 Manufacturing Robotics and Mechatronics (Excl. Automotive Mechatronics)
dc.for 091303 Autonomous Vehicles
dc.personcode 040387
dc.percentage 50 en_US
dc.classification.name Autonomous Vehicles en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom IEEE/RSJ International Conference on Intelligent Robots and Systems en_US
dc.date.activity 20020930 en_US
dc.date.activity 2002-09-30
dc.location.activity Switzerland en_US
dc.description.keywords Kalman filters , computer vision , computerised navigation , edge detection , feature extraction , laser ranging , object recognition , road vehicles en_US
dc.description.keywords Kalman filters , computer vision , computerised navigation , edge detection , feature extraction , laser ranging , object recognition , road vehicles
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history General (ID: 2)


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