1. T.T.Q. Bui, K.-S. Hong, A comparison of using probabilistic motion models for mobile robot pose estimation, vol. 09 (2009), pp. 528–532
2. S. Thrun, W. Burgard, D. Fox, Probabilistic Robotics (MIT Press, Cambridge, Mass, 2005)
3. P. Skrzypczyński, D. Belter, M. Nowicki, Modeling spatial uncertainty of point features in feature-based RGB-D SLAM. Mach. Vis. Appl. 29(5), 827–844 (2018)
4. T.D. Larsen, K.L. Hansen, N.A. Andersen, O. Ravn, Design of Kalman filters for mobile robots: evaluation of the kinematic and odometric approach, in Proceedings of IEEE Conference on Control Applications, vol. 2 (IEEE, United States, 1999)
5. N.J. Gordon, D.J. Salmond, A.F.M. Smith, Novel approach to nonlinear/non-gaussian Bayesian state estimation. IEEE Proc. F, Radar Signal Process. 140(2), 107–113 (1993)