Detection of Ascending Stairs using Stereo Vision

Environment perception is an important task in computer vision for many applications in robotics. Especially for robots navigating through different levels of a building, stair detection constitutes an important perception task. In this paper, we propose a stair detection algorithm using range data. Firstly, we introduce a parameter, which describes local surface orientations w.r.t. a global reference. Secondly, a matched filter is used to detect relevant edges in the orientation data. Afterwards, line segments are determined using these edge data which are further used to estimate stairs. The proposed method is invariant against rotations of the sensor. We show that the system can handle typical outdoor stair types and outperforms the accuracy of state-of-the-art stair detection methods. Moreover, the method is used in real time to assist visually impaired people who wear the camera system on a helmet.