Landmark perception planning for mobile robot localization

Abstract

This paper presents a fuzzy perception planner that takes into account the time cost, the suitability of every landmark detection and the different uncertainties the robot encounters along its path for mobile robot localization. The sensor used is a camera with a motorized zoom on a pan and tilt platform and the artificial landmarks are circles detected through normalized gray scale correlation. An extended Kalman filter is used to correct the position and orientation of the vehicle. The resulting self-localization module has been integrated successfully in a more complicated navigation system.