Investigation of ROS based environment modelling and mobile robot position estimation with dead reckoning and uncertainties

Hamzah, Ahmad and Mohamad Heerwan, Peeie and Mohd Syakirin, Ramli and Amir Akramin, Shafie and Mohd Hezri Fazalul, Rahiman (2021) Investigation of ROS based environment modelling and mobile robot position estimation with dead reckoning and uncertainties. In: IEACon 2021 - 2021 IEEE Industrial Electronics and Applications Conference. 2nd IEEE Industrial Electronics and Applications Conference, IEACon 2021 , 22 - 23 November 2021 , Virtual, Online. pp. 19-24.. ISBN 978-172819253-6 (Published)

Pdf
Investigation of ROS based environment modelling.pdf
Restricted to Repository staff only
Download (797kB) | Request a copy

Preview

Pdf
Investigation of ROS based environment modelling and mobile robot position estimation with dead reckoning and uncertainties_ABS.pdf
Download (231kB) | Preview

DOI/Official URL: https://doi.org/10.1109/IEACon51066.2021.9654762

Abstract

This paper aims to investigate Robot Operating System (ROS) based environment modelling and mobile robot position estimation considering dead reckoning and uncertainties. A mobile robot movement is analyzed in a few environment conditions by using Extended Kalman Filter with ROS to identify and examined the mobile robot estimation performance on its surroundings. The heading angle and initial state covariance performance are assessed with different mobile robot movement. The paper is organized mainly to describe the results from both simulation and experiment using Extended Kalman Filter that consists of undetermined and unpredictable environment states. For experimental verification, a Turtlebot3 equipped with a 360-degree LiDAR and IMU is being applied to demonstrate the performance of estimation in a situation that has unknown uncertainties in several conditions. Both simulation and experimental results indicates that state covariance is converging lesser than the initial state covariance in any environmental cases which is in contrast with the literatures. Besides, it is also found that the mobile robot heading angle is important to be accurate at all times for better estimation results.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Dead reckoning; Estimation; Extended kalman filter; Navigation; State covariance
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics
Faculty/Division:	Faculty of Electrical and Electronic Engineering Technology Faculty of Mechanical and Automotive Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	30 Oct 2024 04:40
Last Modified:	30 Oct 2024 04:40
URI:	http://umpir.ump.edu.my/id/eprint/42392
Download Statistic:	View Download Statistics

Actions (login required)

View Item