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
Link To Document :
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