Abstract
Curb detection is an important research topic in environment perception, which is an essential part of unmanned ground vehicle (UGV) operations. In this paper, a new curb detection method using a 2D laser range finder in a semi-structured environment is presented. In the proposed method, firstly, a local Digital Elevation Map (DEM) is built using 2D sequential laser rangefinder data and vehicle state data in a dynamic environment and a probabilistic moving object deletion approach is proposed to cope with the effect of moving objects. Secondly, the curb candidate points are extracted based on the moving direction of the vehicle in the local DEM. Finally, the straight and curved curbs are detected by the Hough transform and the multi-model RANSAC algorithm, respectively. The proposed method can detect the curbs robustly in both static and typical dynamic environments. The proposed method has been verified in real vehicle experiments.
Highlights
Environment perception is a key research direction in the area of unmanned ground vehicle (UGV) development
According to the different features of the curb detection, the existing algorithms are divided into two categories: the first is based on detection of the geometrical features of the curb; the second category is based on image context derived from the monocular vision field
We propose a new curb detection method based on a local Digital Elevation Map (DEM) which is built from
Summary
Environment perception is a key research direction in the area of UGV development. The UGV is expected to navigate autonomously in semi-structured environments such as campus sites, parks, and the urban environment. Researchers have presented some curb detection algorithms using geometrical features which are obtained by laser range finder [3,4,5,6,7,8], stereo vision [9,10,11], TOF Camera [12,13] and structure light [14]. In [3,4], Kodagoda et al used a tilted 2D laser range finder to detect road curbs In this approach, the result of the measurement is predicted with the Kalman filter algorithm. Zhang proposed a road boundary method which are extracted using the elevation information based on the single data frame from the 2D laser range finder in [8], and the method had been verified in the 2007 DARPA Urban Challenge.
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