PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

 

e-ISSN 2231-8526
ISSN 0128-7680

Home / Regular Issue / JST Vol. 25 (S) Jun. 2017 / JST-S0390-2017

 

Fuzzy Logic Based EKF for Mobile Robot Navigation: An Analysis of Different Fuzzy Membership Functions

Hamzah Ahmad and Nur Aqilah Othman

Pertanika Journal of Science & Technology, Volume 25, Issue S, June 2017

Keywords: Fuzzy logic, Kalman Filter, Membership, Mobile robot, Navigation

Published on: 12 Mac 2018

This paper deals with the analysis of different Fuzzy membership type performance for Extended Kalman Filter (EKF) based mobile robot navigation. EKF is known to be incompetent in non-Gaussian noise condition and therefore the technique alone is not sufficient to provide solution. Motivated by this shortcoming, a Fuzzy based EKF is proposed in this paper. Three membership types are considered which includes the triangular, trapezoidal and Gaussian membership types to determine the best estimation results for mobile robot and landmarks locations. Minimal rule design and configuration are also other aspects being considered for analysis purposes. The simulation results suggest that the Gaussian memberships surpassed other membership type in providing the best solution in mobile robot navigation.

ISSN 0128-7680

e-ISSN 2231-8526

Article ID

JST-S0390-2017

Download Full Article PDF

Share this article

Recent Articles