Road Curb and Intersection Detection using a 2D LMS

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Show simple item record Kodagoda, Sarath en_US Wijesoma, W en_US Balasuriya, Arjuna en_US
dc.contributor.editor NA en_US 2010-07-13T08:50:33Z 2010-07-13T08:50:33Z 2002 en_US
dc.identifier 2006007402 en_US
dc.identifier.citation Kodagoda Sarath, Wijesoma W, and Balasuriya Arjuna 2002, 'Road Curb and Intersection Detection using a 2D LMS', IEEE, Switzerland, pp. 19-24. en_US
dc.identifier.issn 0-7803-7398-7 en_US
dc.identifier.other E1UNSUBMIT en_US
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 harnessed 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 the 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. en_US
dc.language en_US
dc.publisher IEEE en_US
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon en_US
dc.title Road Curb and Intersection Detection using a 2D LMS en_US
dc.parent Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2002) en_US
dc.journal.volume 1 en_US
dc.journal.number en_US
dc.publocation Switzerland en_US
dc.identifier.startpage 19 en_US
dc.identifier.endpage 24 en_US FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 091303 en_US
dc.personcode 040387 en_US
dc.personcode 0000026361 en_US
dc.personcode 0000022937 en_US
dc.percentage 50 en_US 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 20020930 en_US
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

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