UNSCENTED KALMAN FILTER POSITION ESTIMATION FOR AN AUTONOMOUS MOBILE ROBOT

The Kalman filters have been widely used for mobile robot navigation and system integration. So that it may operate autonomously, a mobile robot must know where it is. Accurate localization is a key prerequisite for successful navigation in large-scale environments, particularly when global models are used, such as maps, drawings, topological descriptions, and CAD models. This paper presents the localization of a mobile robot using one variation of the traditional Kalman filter: the unscented Kalman filter (UKF). For this purpose the filter was implemented for a known kinematic model of the robot.