Combination of a low cost GPS with visual localization based on a previous map for outdoor navigation

In this work we propose the combination of a low cost GPS with a vision based localization system. Both types of localization complement each other, providing better precision and robustness than using them separately. The visual localization compares traversable regions detected by a camera with regions previously labeled in a map. We create this map by hand from images taken from Google Maps by labelling those regions passable by the robot (e.g. pavement). For the integration of both localization systems we propose the use of a particle filter. We obtained promising preliminary results taken in the surroundings of the Faculty of Computer Science of the University of A Coruña.