Graph optimization approach to range-based localization

In this article, we propose a general graph optimization-based framework for localization, which can accommodate different types of measurements with varying measurement time intervals. Special emphasis will be on range-based localization. Range and trajectory smoothness constraints are constructed...

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Main Authors: Fang, Xu, Wang, Chen, Nguyen, Thien-Minh, Xie, Lihua
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/153701
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1537012021-12-08T08:45:39Z Graph optimization approach to range-based localization Fang, Xu Wang, Chen Nguyen, Thien-Minh Xie, Lihua School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering::Wireless communication systems Graph Optimization Approach Range-Based Localization In this article, we propose a general graph optimization-based framework for localization, which can accommodate different types of measurements with varying measurement time intervals. Special emphasis will be on range-based localization. Range and trajectory smoothness constraints are constructed in a position graph, then the robot trajectory over a sliding window is estimated by a graph-based optimization algorithm. Moreover, convergence analysis of the algorithm is provided, and the effects of the number of iterations and window size in the optimization on the localization accuracy are analyzed. Extensive experiments on quadcopter under a variety of scenarios verify the effectiveness of the proposed algorithm and demonstrate a much higher localization accuracy than the existing range-based localization methods, especially in the altitude direction. Nanyang Technological University National Research Foundation (NRF) Accepted version This work was supported in part by ST Engineering NTU Corporate Laboratory under the NRF Corporate Lab, University Scheme and National Natural Science Foundation of China under Grant 61720106011. 2021-12-08T08:45:39Z 2021-12-08T08:45:39Z 2020 Journal Article Fang, X., Wang, C., Nguyen, T. & Xie, L. (2020). Graph optimization approach to range-based localization. IEEE Transactions On Systems, Man, and Cybernetics: Systems, 51(11), 6830-6841. https://dx.doi.org/10.1109/TSMC.2020.2964713 2168-2216 https://hdl.handle.net/10356/153701 10.1109/TSMC.2020.2964713 11 51 6830 6841 en 61720106011 IEEE Transactions on Systems, Man, and Cybernetics: Systems © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TSMC.2020.2964713 application/pdf
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::Wireless communication systems
Graph Optimization Approach
Range-Based Localization
spellingShingle Engineering::Electrical and electronic engineering::Wireless communication systems
Graph Optimization Approach
Range-Based Localization
Fang, Xu
Wang, Chen
Nguyen, Thien-Minh
Xie, Lihua
Graph optimization approach to range-based localization
description In this article, we propose a general graph optimization-based framework for localization, which can accommodate different types of measurements with varying measurement time intervals. Special emphasis will be on range-based localization. Range and trajectory smoothness constraints are constructed in a position graph, then the robot trajectory over a sliding window is estimated by a graph-based optimization algorithm. Moreover, convergence analysis of the algorithm is provided, and the effects of the number of iterations and window size in the optimization on the localization accuracy are analyzed. Extensive experiments on quadcopter under a variety of scenarios verify the effectiveness of the proposed algorithm and demonstrate a much higher localization accuracy than the existing range-based localization methods, especially in the altitude direction.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Fang, Xu
Wang, Chen
Nguyen, Thien-Minh
Xie, Lihua
format Article
author Fang, Xu
Wang, Chen
Nguyen, Thien-Minh
Xie, Lihua
author_sort Fang, Xu
title Graph optimization approach to range-based localization
title_short Graph optimization approach to range-based localization
title_full Graph optimization approach to range-based localization
title_fullStr Graph optimization approach to range-based localization
title_full_unstemmed Graph optimization approach to range-based localization
title_sort graph optimization approach to range-based localization
publishDate 2021
url https://hdl.handle.net/10356/153701
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