A Stairway Detection Algorithm based on Vision for UGV Stair Climbing

In the paper, we present a vision based algorithm used to guide the unmanned ground vehicles (UGV) for autonomous stairways climbing and implement it on UGV successfully. The reliability of guiding UGV to climb stairs requires evaluating two offset parameters: the position of vehicle on stairs and the orientation angle to stairs. The intention of our algorithm is to estimate these two parameters through extracting the stair edges robustly. To achieve this goal, we apply the Gabor filter to eliminate the influence of the illumination and keep edges, and propose a fast method to remove small lines. Finally we link stair edges, and estimate the offset parameters used to steer the vehicle by RANSAC algorithm. Experiments on various stairways including indoor and outdoor are given in various light conditions. The results validate our algorithm.