Global localization based on corner point

Abstract

Map matching is a type of popular localization approaches for mobile robot autonomous navigation in indoor environment. Global localization is to find the best correspondence between current local map and the global map. Local map and global map are represented with corner points that are sorted in counterclockwise. The relative position relation of corner points is computed in local and global map and used to search matched pairs. Map matching based on ordinal map improves the searching efficiency. Map matching based on relative position relation avoids frequent coordinates transformation. All these techniques have been implemented on our mobile robot ATRVII equipped with 2D laser range scanner SICK.