Abstract
In this paper we present a method of self localization in the RoboCup middle size league based on the field lines. This method estimates position of the robot by using Monte Carlo Localization (MCL). MCL is widely used for mobile robots localization in a known environment due to its good real-time performance and robustness. MCL estimates state of a robot based on sensory data. In our algorithm, the sensory data are distances to field lines, wheels odometry measurements and direction sensor data. It is prone to estimation error in RoboCup games because robots move around fast in the field and crash each other. So we also study recovery methods for estimation error.