Investigating state covariance properties during finite escape time in H∞ filter SLAM

This paper deals with the investigation of finite escape time problem in H∞ Filter based localization and mapping. Finite escape time in H∞ Filter has restricted the technique to be applied as the mobile robot cannot determine its location effectively due to inconsistent information. Therefore, an a...

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Bibliographic Details
Main Authors: Hamzah, Ahmad, Nur Aqilah, Othman, Mohd Mawardi, Saari, Mohd Syakirin, Ramli
Format: Book Section
Language:English
English
English
Published: Springer Singapore 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/22934/
http://umpir.ump.edu.my/id/eprint/22934/
http://umpir.ump.edu.my/id/eprint/22934/
http://umpir.ump.edu.my/id/eprint/22934/2/70.1%20Investigating%20state%20covariance%20properties%20during%20finite%20escape.pdf
http://umpir.ump.edu.my/id/eprint/22934/9/42.%20Investigating%20state%20covariance%20properties%20during%20finite%20escape%20time%20in%20Hoo%20filter%20SLAM.pdf
http://umpir.ump.edu.my/id/eprint/22934/10/42.1%20Investigating%20state%20covariance%20properties%20during%20finite%20escape%20time%20in%20Hoo%20filter%20SLAM.pdf
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Summary:This paper deals with the investigation of finite escape time problem in H∞ Filter based localization and mapping. Finite escape time in H∞ Filter has restricted the technique to be applied as the mobile robot cannot determine its location effectively due to inconsistent information. Therefore, an analysis to improved the current H∞ Filter Three main factors are being considered in this research namely the initial state covariance, the γ values and the type of noises. This paper also proposed a modified H∞ Filter to reduce the finite escape time problem in the estimation. The analysis and simulation results determine that the modified H∞ Filter has better performance compared to the normal H∞ Filter as well as to Kalman Filter for different γ, initial state covariance and works well in non-gaussian noise environment.