The authors describe a road-following system for an autonomous land vehicle, based on range image analysis. The system is divided into two parts: low-level data-driven analysis, followed by high-level model-directed search. The sequence of steps performed in order to detect three-dimensional (3-D) road boundaries is as follows. Range data are first converted from spherical into Cartesian coordinates. A quadric (or planar) surface is then fitted to the neighborhood of each range pixel, using a least squires fit method. Based on this fit, minimum and maximum principal surface curvatures are computed at each point to detect edges. Next, using Hough transform techniques, 3-D local line segments are extracted. Finally, model-directed reasoning is applied to detect the road boundaries.
Road boundary detection in range imagery for an autonomous robot
Strassenranderkennung durch Bildauswertung fuer fahrerlose Fahrzeuge
IEEE Journal of Robotics and Automation ; 4 , 5 ; 515-523
1988
9 Seiten, 22 Quellen
Aufsatz (Zeitschrift)
Englisch
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