Curb Detection Using 2D Range Data in a Campus Environment

Curb detection is an important research topic for unmanned ground vehicle (UGV) navigation. In this paper, a new curb detection method is proposed using a 2D laser range finder in a campus environment. Firstly, a local Digital Elevation Map (DEM) is built with 2D sequential laser range finder data and vehicle state information. Then, the curb candidate points are extracted considering the moving direction of the vehicle in the local DEM. Finally, the 1D Gaussian process regression is firstly used for curb detection, and the initial training curb data are obtained online by the extracted straight curbs. The proposed method has been verified in different scenes with the real vehicle platform, and it can detect the straight and curved curbs robustly in a campus environment.