An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping

This research is concerned with the problem of localizing gas source in indoor environment using a mobile robot. The problem could be seen as similar to the event of hazardous gas leak in a building. Since the environment is often unknown to the robot, the Simultaneous Localization and Mapping (SLA...

Full description

Saved in:

Bibliographic Details
Format:	Thesis
Language:	English
Subjects:	Mobile robots Gas distribution Smell
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/4/Kamarulzaman%20K.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-unimap-77201
record_format	uketd_dc
spelling	my-unimap-772012022-11-25T01:17:25Z An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping Ali Yeon, Md. Shakaff, Prof. Dr. This research is concerned with the problem of localizing gas source in indoor environment using a mobile robot. The problem could be seen as similar to the event of hazardous gas leak in a building. Since the environment is often unknown to the robot, the Simultaneous Localization and Mapping (SLAM) operation is required. Two open source SLAM techniques (i.e. Gmapping and Hector SLAM) were implemented to provide this crucial information. Extensive experiments and analysis on both SLAM techniques yielded that the Hector SLAM is more suitable for gas distribution mapping (GDM) application due to the improved robot pose estimation, less computational requirement and only performs map correction locally. Therefore, the Hector SLAM is combined with Kernel DM+V algorithm to achieve real-time SLAM-GDM for predicting gas source location. Rigorous real-time experiments were conducted to verify the performance of the proposed SLAM-GDM method in an uncontrolled office building with the presence of ethanol emission. The experimental results showed that the prediction of gas source location is often accurate to 0.5 to 2.0m. Furthermore, an Epanechnikov based Kernel DM+V algorithm was also introduced to limit extrapolation range in GDM computations. The observed advantages were lower computational requirement and slightly more accurate prediction on gas source location. More importantly, it was found that the maps produced were able to indicate the areas of unexplored gas distribution and therefore could be used for the robot‘s path planning. The final and the main part of the thesis deals with the effect of ambient temperature and humidity on metal oxide gas sensor (i.e. TGS 2600) response; which could affect the GDM results. Linear regression processes were conducted to create a model to correct the temperature and humidity drift of the gas sensor response. The model (i.e. function) was tested in various configurations and was found to minimize the effects of the two environmental factors on the gas sensor response in different gas concentrations. Finally, two versions of Kernel DM+V/T/H algorithms were proposed and coupled with the drift model to compensate for temperature and humidity variation during the GDM task. The experimental results showed that the Kernel DM+V/T/H algorithms were able to produce more stable gas distribution maps and improve the accuracy of gas source localization prediction by 34%. Universiti Malaysia Perlis (UniMAP) Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77201 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/1/Page%201-24.pdf 07432dfd14f522a443670f4e53b3654c http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/2/Full%20text.pdf 7160adf959c5d140ac6339ed721079dc http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/4/Kamarulzaman%20K.pdf bd7652af1aa2aafe1900191ed0b0b6c4 Universiti Malaysia Perlis (UniMAP) Mobile robots Gas distribution Smell School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	Ali Yeon, Md. Shakaff, Prof. Dr.
topic	Mobile robots Gas distribution Smell
spellingShingle	Mobile robots Gas distribution Smell An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
description	This research is concerned with the problem of localizing gas source in indoor environment using a mobile robot. The problem could be seen as similar to the event of hazardous gas leak in a building. Since the environment is often unknown to the robot, the Simultaneous Localization and Mapping (SLAM) operation is required. Two open source SLAM techniques (i.e. Gmapping and Hector SLAM) were implemented to provide this crucial information. Extensive experiments and analysis on both SLAM techniques yielded that the Hector SLAM is more suitable for gas distribution mapping (GDM) application due to the improved robot pose estimation, less computational requirement and only performs map correction locally. Therefore, the Hector SLAM is combined with Kernel DM+V algorithm to achieve real-time SLAM-GDM for predicting gas source location. Rigorous real-time experiments were conducted to verify the performance of the proposed SLAM-GDM method in an uncontrolled office building with the presence of ethanol emission. The experimental results showed that the prediction of gas source location is often accurate to 0.5 to 2.0m. Furthermore, an Epanechnikov based Kernel DM+V algorithm was also introduced to limit extrapolation range in GDM computations. The observed advantages were lower computational requirement and slightly more accurate prediction on gas source location. More importantly, it was found that the maps produced were able to indicate the areas of unexplored gas distribution and therefore could be used for the robot‘s path planning. The final and the main part of the thesis deals with the effect of ambient temperature and humidity on metal oxide gas sensor (i.e. TGS 2600) response; which could affect the GDM results. Linear regression processes were conducted to create a model to correct the temperature and humidity drift of the gas sensor response. The model (i.e. function) was tested in various configurations and was found to minimize the effects of the two environmental factors on the gas sensor response in different gas concentrations. Finally, two versions of Kernel DM+V/T/H algorithms were proposed and coupled with the drift model to compensate for temperature and humidity variation during the GDM task. The experimental results showed that the Kernel DM+V/T/H algorithms were able to produce more stable gas distribution maps and improve the accuracy of gas source localization prediction by 34%.
format	Thesis
title	An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
title_short	An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
title_full	An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
title_fullStr	An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
title_full_unstemmed	An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
title_sort	improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Mechatronic Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77201/4/Kamarulzaman%20K.pdf
_version_	1776104249271255040

An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping

Similar Items