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Covariance Inflation Method In Ros Based Mobile Robot Navigation

Mobile robot research has risen tremendously, because of their ability in movements, With the highly dynamic environment for robot applications, there has been an increasing demand on mobile robot movement and capabilities of robot motions. In any areas, robotics is an important field of study that...

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Main Author:	Ezzah Naziha, Roslim
Format:	Undergraduates Project Papers
Language:	English
Published:	2022
Subjects:	TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/39939/1/EC18065_EzzahNaziha_ThesisV2%20-%20Ezzah%20naziha.pdf http://umpir.ump.edu.my/id/eprint/39939/
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spelling	my.ump.umpir.399392024-01-09T08:13:48Z http://umpir.ump.edu.my/id/eprint/39939/ Covariance Inflation Method In Ros Based Mobile Robot Navigation Ezzah Naziha, Roslim TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Mobile robot research has risen tremendously, because of their ability in movements, With the highly dynamic environment for robot applications, there has been an increasing demand on mobile robot movement and capabilities of robot motions. In any areas, robotics is an important field of study that applies knowledge from a variety of professions, including mechanics, electronics, and engineering in order to make the robot move in a way that the user desired with addition of a degree of an autonomy. This thesis presented the investigation of state covariance mobile robot with different condition where it illustrates the important of cross-correlation in the case of mobile robot localization. This thesis deals with the Extended Kalman Filter (EKF) as an alternative technique to overcome issues in mobile robot especially in term of localization. of robot, the mobile robot should manage to map and has their own path planning. Moreover, the algorithm of SLAM (Simultaneous Localization and Mapping) is also used together in order to generate map while locate itself in one environment. Therefore, by considering the method used is covariance inflation, it focuses more on decorrelating week subsets to the state covariance is proved to have better performance while reducing computational cost. Then, this thesis also considers the ROS software for the detection and avoidance of obstacles. In mobile robots, navigation is a difficult problem. A mobile robot is compulsory to recognize its specific position and orientation in either a known or unfamiliar environment in order to move and perform its activities. The result has been recorded and analyze for future recommendation and support our theoretical study. 2022-02 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39939/1/EC18065_EzzahNaziha_ThesisV2%20-%20Ezzah%20naziha.pdf Ezzah Naziha, Roslim (2022) Covariance Inflation Method In Ros Based Mobile Robot Navigation. College of Engineering, Universiti Malaysia Pahang Al-Sultan Abdullah.
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
building	UMPSA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang Al-Sultan Abdullah
content_source	UMPSA Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English
topic	TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Ezzah Naziha, Roslim Covariance Inflation Method In Ros Based Mobile Robot Navigation
description	Mobile robot research has risen tremendously, because of their ability in movements, With the highly dynamic environment for robot applications, there has been an increasing demand on mobile robot movement and capabilities of robot motions. In any areas, robotics is an important field of study that applies knowledge from a variety of professions, including mechanics, electronics, and engineering in order to make the robot move in a way that the user desired with addition of a degree of an autonomy. This thesis presented the investigation of state covariance mobile robot with different condition where it illustrates the important of cross-correlation in the case of mobile robot localization. This thesis deals with the Extended Kalman Filter (EKF) as an alternative technique to overcome issues in mobile robot especially in term of localization. of robot, the mobile robot should manage to map and has their own path planning. Moreover, the algorithm of SLAM (Simultaneous Localization and Mapping) is also used together in order to generate map while locate itself in one environment. Therefore, by considering the method used is covariance inflation, it focuses more on decorrelating week subsets to the state covariance is proved to have better performance while reducing computational cost. Then, this thesis also considers the ROS software for the detection and avoidance of obstacles. In mobile robots, navigation is a difficult problem. A mobile robot is compulsory to recognize its specific position and orientation in either a known or unfamiliar environment in order to move and perform its activities. The result has been recorded and analyze for future recommendation and support our theoretical study.
format	Undergraduates Project Papers
author	Ezzah Naziha, Roslim
author_facet	Ezzah Naziha, Roslim
author_sort	Ezzah Naziha, Roslim
title	Covariance Inflation Method In Ros Based Mobile Robot Navigation
title_short	Covariance Inflation Method In Ros Based Mobile Robot Navigation
title_full	Covariance Inflation Method In Ros Based Mobile Robot Navigation
title_fullStr	Covariance Inflation Method In Ros Based Mobile Robot Navigation
title_full_unstemmed	Covariance Inflation Method In Ros Based Mobile Robot Navigation
title_sort	covariance inflation method in ros based mobile robot navigation
publishDate	2022
url	http://umpir.ump.edu.my/id/eprint/39939/1/EC18065_EzzahNaziha_ThesisV2%20-%20Ezzah%20naziha.pdf http://umpir.ump.edu.my/id/eprint/39939/
_version_	1822924068521771008
score	13.232414

Covariance Inflation Method In Ros Based Mobile Robot Navigation

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