An application of the extended Kalman filter for integrated navigation in mobile robotics

Abstract

In this paper the problem of integrated navigation for mobile robotics is addressed. The dynamics of ground robots are nonlinear, as well as the measurement devices. For the purposes of position estimation, a dead reckoning problem with a wheeled mobile robot is considered using a gyro and two wheel encoders. The extended Kalman filter (EKF) is used to provide an estimate of vehicle state, gyro error dynamics and variables describing the slip effects. The parameters of the error dynamics have been identified and validated off-line by real data. Simulations results have confirmed the efficacy of the proposed approach, by comparing the performances of the EKF with and without a wheel slip model.