Adaptive extended Kalman filter (AEKF)-based mobile robot localization using sonar

Abstract

In this paper, an AEKF algorithm is used to localize a mobile robot equipped with eight Polaroid sonars in an indoor structured environment. The system state equation and sonar measurement models used for locating the mobile robot are set up. The localization process based on the AEKF algorithm is given. Four criteria used to judge the validity of predictive measurements of sonars are presented, which can increase the probability of the matching between predictive measurements and actual measurements. Experiments show that the localization precision based on our methods is greater than that using the conventional EKF algorithm.