Robust localization using RGB-D images

Visual information extracted from RGB images has been successfully used for mobile robot localization. The main difficulty with localization using RGB images is that visual features from RGB images are not completely invariant against changes in viewpoints and lighting conditions. This problem can be overcome using features from RGB-D images. In this paper, we evaluate two depth features, depth patches and histograms of oriented normal vectors, extracted from RGB-D images for localization of a mobile robot and demonstrate that robust localization is possible under varying lighting conditions.