Abstract
Staircase detection in an important ability required by indoor robots, allowing for multi-floor exploration in 3D environments. We present an algorithm for stair-case detection from point-cloud data based on a new minimal 3D map representation and the estimation of step-like features that are grouped based on adjacency in order to emerge dominant staircase structures. Experiments performed using noisy RGB-D sensor data from robot exploration trials showed a reliable detection performance under varying conditions.