Dual-user localization using ARKit and nearby interaction for iOS devices

This dissertation delves into the burgeoning field of indoor ranging and dualuser Augmented Reality (AR) techniques, primarily focusing on the integration and comparison of Visual Inertial Odometry (VIO) and Ultra-Wideband (UWB) technologies. The motivation behind this research stems from the need t...

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Main Author: Zhang, Yuyang
Other Authors: Ling Keck Voon
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2024
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Online Access:https://hdl.handle.net/10356/174837
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1748372024-04-19T15:58:03Z Dual-user localization using ARKit and nearby interaction for iOS devices Zhang, Yuyang Ling Keck Voon School of Electrical and Electronic Engineering EKVLING@ntu.edu.sg Engineering Visual inertial Odometry Ultra-wideband Indoor localization Kalman filter This dissertation delves into the burgeoning field of indoor ranging and dualuser Augmented Reality (AR) techniques, primarily focusing on the integration and comparison of Visual Inertial Odometry (VIO) and Ultra-Wideband (UWB) technologies. The motivation behind this research stems from the need to improve accuracy and stability in indoor ranging systems, particularly for dual-user AR applications. The study systematically explores the advantages and limitations of VIO and UWB localization in various indoor environments, employing rigorous experimental methods to assess their performance under different conditions. Significant emphasis is placed on the development and application of a Kalman filter-based approach to fuse the data from both VIO and UWB ranging, aiming to enhance the overall accuracy and stability of indoor ranging. The results demonstrate notable improvements in distance estimation precision and positioning stability, highlighting the potential of this integrated approach for future dual-user AR applications. This work not only contributes to the advancement of indoor ranging technologies but also sets a foundation for further exploration in dual-user AR environments. Master's degree 2024-04-15T03:50:15Z 2024-04-15T03:50:15Z 2023 Thesis-Master by Coursework Zhang, Y. (2023). Dual-user localization using ARKit and nearby interaction for iOS devices. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/174837 https://hdl.handle.net/10356/174837 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
Visual inertial
Odometry
Ultra-wideband
Indoor localization
Kalman filter
spellingShingle Engineering
Visual inertial
Odometry
Ultra-wideband
Indoor localization
Kalman filter
Zhang, Yuyang
Dual-user localization using ARKit and nearby interaction for iOS devices
description This dissertation delves into the burgeoning field of indoor ranging and dualuser Augmented Reality (AR) techniques, primarily focusing on the integration and comparison of Visual Inertial Odometry (VIO) and Ultra-Wideband (UWB) technologies. The motivation behind this research stems from the need to improve accuracy and stability in indoor ranging systems, particularly for dual-user AR applications. The study systematically explores the advantages and limitations of VIO and UWB localization in various indoor environments, employing rigorous experimental methods to assess their performance under different conditions. Significant emphasis is placed on the development and application of a Kalman filter-based approach to fuse the data from both VIO and UWB ranging, aiming to enhance the overall accuracy and stability of indoor ranging. The results demonstrate notable improvements in distance estimation precision and positioning stability, highlighting the potential of this integrated approach for future dual-user AR applications. This work not only contributes to the advancement of indoor ranging technologies but also sets a foundation for further exploration in dual-user AR environments.
author2 Ling Keck Voon
author_facet Ling Keck Voon
Zhang, Yuyang
format Thesis-Master by Coursework
author Zhang, Yuyang
author_sort Zhang, Yuyang
title Dual-user localization using ARKit and nearby interaction for iOS devices
title_short Dual-user localization using ARKit and nearby interaction for iOS devices
title_full Dual-user localization using ARKit and nearby interaction for iOS devices
title_fullStr Dual-user localization using ARKit and nearby interaction for iOS devices
title_full_unstemmed Dual-user localization using ARKit and nearby interaction for iOS devices
title_sort dual-user localization using arkit and nearby interaction for ios devices
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/174837
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