Mobile robot localization in geometrically symmetric environments

With the rapid development of mobile robots in recent years, the demand for localization and positioning algorithms is getting higher and higher. Although there are already localization algorithms that can successfully localize the mobile robots in certain environments, mobile robots localization is...

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Main Author: Lyu, Yaozeng
Other Authors: Wang Dan Wei
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/155002
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1550022023-07-04T16:42:03Z Mobile robot localization in geometrically symmetric environments Lyu, Yaozeng Wang Dan Wei School of Electrical and Electronic Engineering EDWWANG@ntu.edu.sg Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics With the rapid development of mobile robots in recent years, the demand for localization and positioning algorithms is getting higher and higher. Although there are already localization algorithms that can successfully localize the mobile robots in certain environments, mobile robots localization is still a challenging task in geometrically repetitive and symmetrical environments. At present, the most used global localization method is based on the Global Navigation Satellite System (GNSS). However, when it comes to semi-indoor or indoor situations, the GNSS signal will become unstable, resulting in localization failures. Other commonly used localization methods are based on camera or Light Detection and Ranging (LiDAR) onboard the mobile robots. However, extremely similar and ambiguous environments make these methods difficult to accomplish the localization tasks. In recent years, the ambient magnetic field-based localization has proven to be a feasible solution due to its pervasiveness and ease of implementation, where meter-level accuracy has been achieved in semi-indoor or indoor environments. Therefore, this project aims to propose a magnetic field-based localization system to solve the problem of mobile robots localization issues in highly symmetric environments. At present, the magnetic field-based localization method still faces many problems, such as dependence on the rotation-sensitive magnetic field components, low accuracy in relatively large-scale environments, etc. In addition, the similar magnetic field single fingerprint information can easily cause mismatches in the magnetic field map, then lead to localization failures. This project will explore and propose novel magnetic field-based localization algorithms for mobile robots to achieve highly robust and precise localization in geometrically symmetric environment. Master of Science (Computer Control and Automation) 2022-01-28T03:16:53Z 2022-01-28T03:16:53Z 2021 Thesis-Master by Coursework Lyu, Y. (2021). Mobile robot localization in geometrically symmetric environments. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/155002 https://hdl.handle.net/10356/155002 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
spellingShingle Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Lyu, Yaozeng
Mobile robot localization in geometrically symmetric environments
description With the rapid development of mobile robots in recent years, the demand for localization and positioning algorithms is getting higher and higher. Although there are already localization algorithms that can successfully localize the mobile robots in certain environments, mobile robots localization is still a challenging task in geometrically repetitive and symmetrical environments. At present, the most used global localization method is based on the Global Navigation Satellite System (GNSS). However, when it comes to semi-indoor or indoor situations, the GNSS signal will become unstable, resulting in localization failures. Other commonly used localization methods are based on camera or Light Detection and Ranging (LiDAR) onboard the mobile robots. However, extremely similar and ambiguous environments make these methods difficult to accomplish the localization tasks. In recent years, the ambient magnetic field-based localization has proven to be a feasible solution due to its pervasiveness and ease of implementation, where meter-level accuracy has been achieved in semi-indoor or indoor environments. Therefore, this project aims to propose a magnetic field-based localization system to solve the problem of mobile robots localization issues in highly symmetric environments. At present, the magnetic field-based localization method still faces many problems, such as dependence on the rotation-sensitive magnetic field components, low accuracy in relatively large-scale environments, etc. In addition, the similar magnetic field single fingerprint information can easily cause mismatches in the magnetic field map, then lead to localization failures. This project will explore and propose novel magnetic field-based localization algorithms for mobile robots to achieve highly robust and precise localization in geometrically symmetric environment.
author2 Wang Dan Wei
author_facet Wang Dan Wei
Lyu, Yaozeng
format Thesis-Master by Coursework
author Lyu, Yaozeng
author_sort Lyu, Yaozeng
title Mobile robot localization in geometrically symmetric environments
title_short Mobile robot localization in geometrically symmetric environments
title_full Mobile robot localization in geometrically symmetric environments
title_fullStr Mobile robot localization in geometrically symmetric environments
title_full_unstemmed Mobile robot localization in geometrically symmetric environments
title_sort mobile robot localization in geometrically symmetric environments
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/155002
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