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Data association analysis in simultaneous localization and mapping problem

Hamzah, Ahmad and Nur Aqilah, Othman and Mohd Mawardi, Saari and Mohd Syakirin, Ramli and Bakiss Hiyana, Abu Bakar (2018) Data association analysis in simultaneous localization and mapping problem. In: International Conference On Artificial Intelligence And Robotics For Industrial Applications 2018 (AIR2018), 28-29 November 2018 , Putrajaya, Malaysia. pp. 1-7.. (Unpublished)

95.1 Data association analysis in simultaneous localization.pdf

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This paper examines the data association issues in Simultaneous Localization and Mapping Problem on two different techniques. Data association determines the system efficiency and there are limited numbers of papers attempts to analyze the conditions. Two filters namely the Extended Kalman Filter(EKF) and H∞ Filters are considered in this paper to improved the estimation results of both mobile robot and the environment locations. The updated state covariance is modified to obtain better performance compared to its original state. The simulation results have shown consistency and lower percentage of errors for the proposed technique. However, there are certain cases that showing the updated state covariance becomes unstable and yields erroneous results especially for EKF. Hence, further works are expected to be carried for this matter.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: EKF; H∞ Filters; Simultaneous Localization and Mapping; State Covariance; Data association
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 18 Oct 2019 01:13
Last Modified: 18 Oct 2019 01:13
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