Grid-based localization of a mobile robot using sonar sensors

Abstract

This paper presents a technique for localization of a mobile robot using sonar sensors. Localization is the continual provision of knowledges of position that are deduced from its a priori position estimation. The environment of a robot is modeled by a two-dimensional grid map. We define a physically based sonar sensor model and employ an extended Kalman filter to estimate positions of the robot. Since the approach does not rely on an exact geometric model of an object, it is very simple and offers sufficient generality such that integration with concurrent mapping and localization can be achieved without major modifications. The performance and simplicity of the approach are demonstrated with the results produced by sets of experiments using a mobile robot equipped with sonar sensors.