Kalman filters predictive steps comparison for vehicle localization

The aim of this paper is to perform a comparison among several different Kalman filters algorithms designed for nonlinear systems. After presenting the most popular of them and showing its limitations, we introduce some new Kalman filters in order to compare them in the vehicle localization context. This comparison is based on the sole use of their predictive steps that corresponds to the worst case that it can occur in vehicle localization (corrective data are unavailable).

[1]  Nadine Le Fort-Piat,et al.  Safe Task Planning Integrating Uncertainties and Local Maps Federations , 2000, Int. J. Robotics Res..

[2]  Peter Cheeseman,et al.  On the Representation and Estimation of Spatial Uncertainty , 1986 .

[3]  M. Nørgaard,et al.  Advances in Derivative-Free State Estimation for Nonlinear Systems , 1998 .

[4]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[5]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[6]  James L. Crowley,et al.  World modeling and position estimation for a mobile robot using ultrasonic ranging , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[7]  S. Julier,et al.  A General Method for Approximating Nonlinear Transformations of Probability Distributions , 1996 .

[8]  Sebastien Glaser,et al.  LATERAL DRIVING ASSISTANCE USING ROBUST CONTROL AND EMBEDDED DRIVER-VEHICLE-ROAD MODEL , 2004 .

[9]  Stergios I. Roumeliotis,et al.  Extended Kalman filter for frequent local and infrequent global sensor data fusion , 1997, Other Conferences.

[10]  J. L. Roux.  An Introduction to the Kalman Filter , 2003 .

[11]  Herman Bruyninckx,et al.  Kalman filters for non-linear systems: a comparison of performance , 2004 .

[12]  Kazufumi Ito,et al.  Gaussian filters for nonlinear filtering problems , 2000, IEEE Trans. Autom. Control..

[13]  F. Gustafsson,et al.  Model-based statistical tracking and decision making for collision avoidance application , 2004, Proceedings of the 2004 American Control Conference.

[14]  Nando de Freitas,et al.  The Unscented Particle Filter , 2000, NIPS.