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Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints

This paper presents a practical yet effective solution for integrating an RGB-D camera and an inertial sensor to handle the depth dropouts that frequently happen in outdoor environments, due to the short detection range and sunlight interference. In depth drop conditions, only the partial 5-degrees-...

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Detalles Bibliográficos
Autores principales: Qayyum, Usman, Kim, Jonghyuk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434182/
https://www.ncbi.nlm.nih.gov/pubmed/34502806
http://dx.doi.org/10.3390/s21175913
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author Qayyum, Usman
Kim, Jonghyuk
author_facet Qayyum, Usman
Kim, Jonghyuk
author_sort Qayyum, Usman
collection PubMed
description This paper presents a practical yet effective solution for integrating an RGB-D camera and an inertial sensor to handle the depth dropouts that frequently happen in outdoor environments, due to the short detection range and sunlight interference. In depth drop conditions, only the partial 5-degrees-of-freedom pose information (attitude and position with an unknown scale) is available from the RGB-D sensor. To enable continuous fusion with the inertial solutions, the scale ambiguous position is cast into a directional constraint of the vehicle motion, which is, in essence, an epipolar constraint in multi-view geometry. Unlike other visual navigation approaches, this can effectively reduce the drift in the inertial solutions without delay or under small parallax motion. If a depth image is available, a window-based feature map is maintained to compute the RGB-D odometry, which is then fused with inertial outputs in an extended Kalman filter framework. Flight results from the indoor and outdoor environments, as well as public datasets, demonstrate the improved navigation performance of the proposed approach.
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spelling pubmed-84341822021-09-12 Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints Qayyum, Usman Kim, Jonghyuk Sensors (Basel) Article This paper presents a practical yet effective solution for integrating an RGB-D camera and an inertial sensor to handle the depth dropouts that frequently happen in outdoor environments, due to the short detection range and sunlight interference. In depth drop conditions, only the partial 5-degrees-of-freedom pose information (attitude and position with an unknown scale) is available from the RGB-D sensor. To enable continuous fusion with the inertial solutions, the scale ambiguous position is cast into a directional constraint of the vehicle motion, which is, in essence, an epipolar constraint in multi-view geometry. Unlike other visual navigation approaches, this can effectively reduce the drift in the inertial solutions without delay or under small parallax motion. If a depth image is available, a window-based feature map is maintained to compute the RGB-D odometry, which is then fused with inertial outputs in an extended Kalman filter framework. Flight results from the indoor and outdoor environments, as well as public datasets, demonstrate the improved navigation performance of the proposed approach. MDPI 2021-09-02 /pmc/articles/PMC8434182/ /pubmed/34502806 http://dx.doi.org/10.3390/s21175913 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Qayyum, Usman
Kim, Jonghyuk
Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints
title Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints
title_full Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints
title_fullStr Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints
title_full_unstemmed Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints
title_short Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints
title_sort depth-camera-aided inertial navigation utilizing directional constraints
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434182/
https://www.ncbi.nlm.nih.gov/pubmed/34502806
http://dx.doi.org/10.3390/s21175913
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