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Full-Text Articles in Physical Sciences and Mathematics
Stability Of The Adaptive Fading Extended Kalman Filter With The Matrix Forgetting Factor, Cenker Bi̇çer, Esi̇n Köksal Babacan, Levent Özbek
Stability Of The Adaptive Fading Extended Kalman Filter With The Matrix Forgetting Factor, Cenker Bi̇çer, Esi̇n Köksal Babacan, Levent Özbek
Turkish Journal of Electrical Engineering and Computer Sciences
The extended Kalman filter is extensively used in nonlinear state estimation problems. As long as the system characteristics are correctly known, the extended Kalman filter gives the best performance. However, when the system information is partially known or incorrect, the extended Kalman filter may diverge or give biased estimates. An extensive number of works has been published to improve the performance of the extended Kalman filter. Many researchers have proposed the introduction of a forgetting factor, both into the Kalman filter and the extended Kalman filter, to improve the performance. However, there are 2 fundamental problems with this approach: the …
An Improved Fastslam Framework Using Soft Computing, Ramazan Havangi, Mohammad Ali Nekoui, Mohammad Teshnehlab
An Improved Fastslam Framework Using Soft Computing, Ramazan Havangi, Mohammad Ali Nekoui, Mohammad Teshnehlab
Turkish Journal of Electrical Engineering and Computer Sciences
FastSLAM is a framework for simultaneous localization and mapping (SLAM) using a Rao-Blackwellized particle filter. However, FastSLAM degenerates over time. This degeneracy is due to the fact that a particle set estimating the pose of the robot loses its diversity. One of the main reasons for losing particle diversity in FastSLAM is sample impoverishment. In this case, most of the particle weights are insignificant. Another problem of FastSLAM relates to the design of an extended Kalman filter (EKF) for the landmark position's estimation. The performance of the EKF and the quality of the estimation depend heavily on correct a priori …