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An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2

This is an adaptive Mobile Robot Navigation project based on Fuzzy Logic Type 2. The goal of this study is to investigate the performance of a mobile robot in an environment (navigation). As a result, this project will be emphasized on the outcomes of simulation for the mobile robot in navigation. T...

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Main Author: Siti Nur Aliza, Azmi
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/39871/1/EA18020%20ALIZA%20AZMI%20-%20PSM2%20THESIS%20FULL%20-%20Siti%20Nur%20Aliza%20Azmi.pdf
http://umpir.ump.edu.my/id/eprint/39871/
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spelling my.ump.umpir.398712024-01-05T04:16:43Z http://umpir.ump.edu.my/id/eprint/39871/ An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2 Siti Nur Aliza, Azmi TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering This is an adaptive Mobile Robot Navigation project based on Fuzzy Logic Type 2. The goal of this study is to investigate the performance of a mobile robot in an environment (navigation). As a result, this project will be emphasized on the outcomes of simulation for the mobile robot in navigation. The background for the simulation will be based on the obstacle avoidance. In brief, when the fuzzy controller detects any potential obstacle nearer or on the way for the robot going to the goal point, the robot will be able to avoid it. In navigation, the surrounding environment for the robot and the position of the obstacle should be understood ahead of time. The robot is required to navigate to its destination by avoiding the obstacle. In such, the robot navigation in simulations can be estimated using prior information of the coordinates from the beginning point, the goal point, and the obstacle position. Thus, in this research, the cost function method was implemented to evaluate and estimate the robot's surroundings in a simulated environment. Consequently, the objective of the project is to design a mobile robot in navigation using the fuzzy logic system and to develop the lower state estimation error for both estimated and measured simulation value. By using the cost function and fuzzy logic, the mobile robot navigation was proved as the result shows that the robot was able to avoid the obstacle on its way toward the goal point. Furthermore, the graph shows only a slight difference occurred between the measured and estimated values, indicating that the project was implemented as required. 2022-02 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39871/1/EA18020%20ALIZA%20AZMI%20-%20PSM2%20THESIS%20FULL%20-%20Siti%20Nur%20Aliza%20Azmi.pdf Siti Nur Aliza, Azmi (2022) An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2. 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
Siti Nur Aliza, Azmi
An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2
description This is an adaptive Mobile Robot Navigation project based on Fuzzy Logic Type 2. The goal of this study is to investigate the performance of a mobile robot in an environment (navigation). As a result, this project will be emphasized on the outcomes of simulation for the mobile robot in navigation. The background for the simulation will be based on the obstacle avoidance. In brief, when the fuzzy controller detects any potential obstacle nearer or on the way for the robot going to the goal point, the robot will be able to avoid it. In navigation, the surrounding environment for the robot and the position of the obstacle should be understood ahead of time. The robot is required to navigate to its destination by avoiding the obstacle. In such, the robot navigation in simulations can be estimated using prior information of the coordinates from the beginning point, the goal point, and the obstacle position. Thus, in this research, the cost function method was implemented to evaluate and estimate the robot's surroundings in a simulated environment. Consequently, the objective of the project is to design a mobile robot in navigation using the fuzzy logic system and to develop the lower state estimation error for both estimated and measured simulation value. By using the cost function and fuzzy logic, the mobile robot navigation was proved as the result shows that the robot was able to avoid the obstacle on its way toward the goal point. Furthermore, the graph shows only a slight difference occurred between the measured and estimated values, indicating that the project was implemented as required.
format Undergraduates Project Papers
author Siti Nur Aliza, Azmi
author_facet Siti Nur Aliza, Azmi
author_sort Siti Nur Aliza, Azmi
title An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2
title_short An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2
title_full An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2
title_fullStr An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2
title_full_unstemmed An Adaptive Mobile Robot with Gaussian type on Fuzzy Logic Type 2
title_sort adaptive mobile robot with gaussian type on fuzzy logic type 2
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39871/1/EA18020%20ALIZA%20AZMI%20-%20PSM2%20THESIS%20FULL%20-%20Siti%20Nur%20Aliza%20Azmi.pdf
http://umpir.ump.edu.my/id/eprint/39871/
_version_ 1822924031609798656
score 13.232414

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