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FEKF Estimation for Mobile Robot Localization and Mapping Considering Noise Divergence

Hamzah, Ahmad and Nur Aqilah, Othman and Saifudin, Razali and Mohd Razali, Daud (2016) FEKF Estimation for Mobile Robot Localization and Mapping Considering Noise Divergence. In: Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2015, 11-13 October 2015 , Johor Bahru, Johor, Malaysia. .

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Abstract

This paper proposed an approach of Fuzzy-Extended Kalman Filter(FEKF) for mobile robot localization and mapping under unknown noise characteristics. The technique apply the information extracted from EKF measurement innovation to derive the best estimation output for a mobile robot during its observations. These information is then fuzzified using Fuzzy Logic technique with very few design rules to control the information which at the end further reducing the error about the measurement and consequently provide better localization and mapping. Simulation results are also presented to describe the efficiency of the proposed method in comparison with the normal EKF estimation that emphasize FEKF exceeds the estimation results of normal EKF in non-Gaussian noise environment.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Fuzzy Logic; Kalman Filter; Mobile Robot Localization; Mapping
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 20 Nov 2015 03:27
Last Modified: 05 Sep 2018 04:32
URI: http://umpir.ump.edu.my/id/eprint/11195
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