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An Approach to Reduce Computational Cost for Localization Problem

Nur Aqilah, Othman and Hamzah, Ahmad (2014) An Approach to Reduce Computational Cost for Localization Problem. In: Colloquium on Robotics, Unmanned Systems And Cybernetics 2014 (CRUSC 2014), 20 Nov 2014 , Universiti Malaysia Pahang. pp. 37-43..

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Abstract

One of the biggest factors that contribute to the computational cost of extended Kalman filter-based SLAM is the covariance update. This is due to the multiplications of the covariance matrix with other parameters and the increment of its dimension, which is twice the number of landmarks. Therefore a study is conducted to find a possible technique to decrease the computational complexity of the covariance matrix without minimizing the accuracy of the state estimation. This paper presents a preliminary study on the matrixdiagonalization technique, which is applied to the covariance matrix in EKF-based SLAM to simplify the multiplication process. The behaviors of estimation and covariance are observed based on three case studies.

Item Type: Conference or Workshop Item (Speech)
Uncontrolled Keywords: covariance, diagonalization, extendedKalman filter, simultaneous localization and mapping.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mr. Mohd Fakhrurrazi Adnan
Date Deposited: 14 Mar 2016 02:07
Last Modified: 05 Feb 2018 07:13
URI: http://umpir.ump.edu.my/id/eprint/9786
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