A laser scanner based mobile robot SLAM algorithm with improved convergence properties

Abstract

We have developed a laser scanner based simultaneous localization and map building method, specifically addressing the divergence problem of the classical extended Kalman filters (EKF) based simultaneous localization and map building (SLAM) algorithms. Our method utilizes two EKFs. The first is used to estimate the orientations of the robot and the obstacles, and the second estimates the positions of the robot and of the obstacles. Experimental results are also presented to verify our arguments.