Mobile Robot Localization based on a Polynomial Approach

This paper introduces a new analytical algorithm to perform the localization of a mobile robot using odometry and laser readings. Based on a polynomial approach, the proposed algorithm provides the optimal affine filter in a class of suitably defined estimators. The performance of the algorithm has been evaluated through simulations. The comparison with the standard extended Kalman filter shows that the proposed filter provides good estimates also in critical situations where the system nonlinearities cause a bad behavior of the EKF.