Abstract
Environment perception is essential for autonomous driving technology. The curb is a prominent feature of urban roads and therefore is a significant part of environment perception. In this paper, a real-time curb detection and tracking method is proposed for Unmanned Ground Vehicles (UGVs). The proposed curb detection algorithm uses the the surrounding environment data provided by a 3D-LIDAR sensor to extract the curb position based on its spatial features. The curb tracking algorithm is proposed to predict and update the curb position with respect to the current vehicle states in real time. The performance of the proposed method is verified through extensive experiments with a UGV driving on campus roads. The experimental results demonstrate the accuracy and robustness of the proposed method.
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