DocumentCode
1001578
Title
Road-boundary detection and tracking using ladar sensing
Author
Wijesoma, W.S. ; Kodagoda, K.R.S. ; Balasuriya, Arjuna P.
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume
20
Issue
3
fYear
2004
fDate
6/1/2004 12:00:00 AM
Firstpage
456
Lastpage
464
Abstract
Road-boundary detection is an integral and important function in advanced driver-assistance systems and autonomous vehicle navigation systems. A prominent feature of roads in urban, semi-urban, and similar environments, such as in theme parks, campus sites, industrial estates, science parks, and the like, is curbs on either side defining the road´s boundary. Although vision is the most common and popular sensing modality used by researchers and automotive manufacturers for road-lane detection, it can pose formidable challenges in detecting road curbs under poor illumination, bad weather, and complex driving environments. This paper proposes a novel method based on extended Kalman filtering for fast detection and tracking of road curbs using successive range/bearing readings obtained from a scanning two-dimensional ladar measurement system. As compared with millimeter wave radar methods reported in the literature, the proposed technique is simpler and computationally more efficient. This is the first of its kind reported in the literature. Qualitative experimental results are presented from the application of the technique to a campus site environment to demonstrate the viability, effectiveness, and robustness.
Keywords
Kalman filters; computerised navigation; driver information systems; laser ranging; nonlinear filters; optical radar; road vehicles; roads; traffic engineering computing; advanced driver assistance system; autonomous vehicle navigation system; extended Kalman filter; ladar measurement system; range readings; road boundary detection; road lane tracking; Laser radar; Millimeter wave radar; Mobile robots; Navigation; Radar detection; Radar tracking; Remotely operated vehicles; Road vehicles; Vehicle detection; Vehicle driving; Autonomous vehicles; feature extraction; laser radar; robot sensing systems;
fLanguage
English
Journal_Title
Robotics and Automation, IEEE Transactions on
Publisher
ieee
ISSN
1042-296X
Type
jour
DOI
10.1109/TRA.2004.825269
Filename
1303691
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