Localization based on region descriptors in grid maps

This paper presents a novel approach towards highly precise self-localization of a vehicle on a digital map. The proposed approach utilizes a map containing region descriptors extracted from ordinary occupancy grid maps. The Maximally Stable Extremal Regions (MSER) algorithm provides robust feature extraction from grid maps in a completely unsupervised process. This allows for the automatic creation of huge maps. Since only single region descriptor points of grid maps are saved in the map database, the data volume of the produced map is kept low. The approach uses a particle filter to estimate the vehicle position on the digital map. The particle filter associates MSER features extracted from an online generated grid map with features of the digital map. An evaluation with real world sensor data, collected on a German rural road, shows that the approach locates the vehicle very precisely.