Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot

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

Improving Covariance Matrix.pdf

Download (165kB) | Preview


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.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Part of the Lecture Notes in Electrical Engineering book series (LNEE)
Uncontrolled Keywords: Covariance, Diagonalization, Pseudo
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Institute of Postgraduate Studies
College of Engineering
Faculty of Electrical and Electronic Engineering Technology
Depositing User: Noorul Farina Arifin
Date Deposited: 29 Nov 2021 03:28
Last Modified: 29 Nov 2021 03:28
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item