Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot

Diagonalization of covariance matrix through eigenvalue approach in extended Kalman Filter (EKF)-based simultaneous localization and mapping (SLAM) of mobile robot has been studied, as one of the possible approaches in reducing complexity hence computational cost of the system. However, the estimati...

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Main Authors: Maziatun, Mohamad Mazlan, Nur Aqilah, Othman, Hamzah, Ahmad
Format: Conference or Workshop Item
Language:English
Published: Springer 2022
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/32672/1/Improving%20Covariance%20Matrix.pdf
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author Maziatun, Mohamad Mazlan
Nur Aqilah, Othman
Hamzah, Ahmad
author_facet Maziatun, Mohamad Mazlan
Nur Aqilah, Othman
Hamzah, Ahmad
author_sort Maziatun, Mohamad Mazlan
collection UMP
description Diagonalization of covariance matrix through eigenvalue approach in extended Kalman Filter (EKF)-based simultaneous localization and mapping (SLAM) of mobile robot has been studied, as one of the possible approaches in reducing complexity hence computational cost of the system. However, the estimation is seemed to be too optimistic, and further investigation need to be conducted. In this paper, the effect on addition of Pseudo elements in the diagonalization process is investigated. It is evaluated at the updated state covariance matrix of EKF-based SLAM. It is found that the additional of pseudo components in diagonal matrix can improve the covariance matrix and lower the computational complexity. This finding has been proved through simulation.
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spelling UMPir326722021-11-29T03:28:25Z http://umpir.ump.edu.my/id/eprint/32672/ Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot Maziatun, Mohamad Mazlan Nur Aqilah, Othman Hamzah, Ahmad TK Electrical engineering. Electronics Nuclear engineering Diagonalization of covariance matrix through eigenvalue approach in extended Kalman Filter (EKF)-based simultaneous localization and mapping (SLAM) of mobile robot has been studied, as one of the possible approaches in reducing complexity hence computational cost of the system. However, the estimation is seemed to be too optimistic, and further investigation need to be conducted. In this paper, the effect on addition of Pseudo elements in the diagonalization process is investigated. It is evaluated at the updated state covariance matrix of EKF-based SLAM. It is found that the additional of pseudo components in diagonal matrix can improve the covariance matrix and lower the computational complexity. This finding has been proved through simulation. Springer 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/32672/1/Improving%20Covariance%20Matrix.pdf Maziatun, Mohamad Mazlan and Nur Aqilah, Othman and Hamzah, Ahmad (2022) Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot. In: Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020: NUSYS’20 , 27-28 October 2020 , Virtually via the IEEE OES Malaysia Virtual/Online Conference Platform. pp. 995-1007., 770. ISBN 978-981-16-2406-3 (Published) https://doi.org/10.1007/978-981-16-2406-3_73
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Maziatun, Mohamad Mazlan
Nur Aqilah, Othman
Hamzah, Ahmad
Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot
title Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot
title_full Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot
title_fullStr Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot
title_full_unstemmed Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot
title_short Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot
title_sort improving covariance matrix diagonalization in slam of mobile robot
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/32672/1/Improving%20Covariance%20Matrix.pdf
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