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IMU Networks for Trajectory Reconstruction in Logistics Applications

This paper discusses the use of networks of Inertial Measurement Units (IMUs) for the reconstruction of trajectories from sensor data. Logistics is a natural application domain to verify the quality of the handling of goods. This is a mass application and the economics of logistics impose that the I...

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Autor principal: Sequeira, João Silva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535935/
https://www.ncbi.nlm.nih.gov/pubmed/37765895
http://dx.doi.org/10.3390/s23187838
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author Sequeira, João Silva
author_facet Sequeira, João Silva
author_sort Sequeira, João Silva
collection PubMed
description This paper discusses the use of networks of Inertial Measurement Units (IMUs) for the reconstruction of trajectories from sensor data. Logistics is a natural application domain to verify the quality of the handling of goods. This is a mass application and the economics of logistics impose that the IMUs to be used must be low-cost and use basic computational devices. The approach in this paper converts a strategy from the literature, used in the multi-target following problem, to reach a consensus in a network of IMUs. This paper presents results on how to achieve the consensus in trajectory reconstruction, along with covariance intersection data fusion of the information obtained by all the nodes in the network.
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spelling pubmed-105359352023-09-29 IMU Networks for Trajectory Reconstruction in Logistics Applications Sequeira, João Silva Sensors (Basel) Article This paper discusses the use of networks of Inertial Measurement Units (IMUs) for the reconstruction of trajectories from sensor data. Logistics is a natural application domain to verify the quality of the handling of goods. This is a mass application and the economics of logistics impose that the IMUs to be used must be low-cost and use basic computational devices. The approach in this paper converts a strategy from the literature, used in the multi-target following problem, to reach a consensus in a network of IMUs. This paper presents results on how to achieve the consensus in trajectory reconstruction, along with covariance intersection data fusion of the information obtained by all the nodes in the network. MDPI 2023-09-12 /pmc/articles/PMC10535935/ /pubmed/37765895 http://dx.doi.org/10.3390/s23187838 Text en © 2023 by the author. 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
Sequeira, João Silva
IMU Networks for Trajectory Reconstruction in Logistics Applications
title IMU Networks for Trajectory Reconstruction in Logistics Applications
title_full IMU Networks for Trajectory Reconstruction in Logistics Applications
title_fullStr IMU Networks for Trajectory Reconstruction in Logistics Applications
title_full_unstemmed IMU Networks for Trajectory Reconstruction in Logistics Applications
title_short IMU Networks for Trajectory Reconstruction in Logistics Applications
title_sort imu networks for trajectory reconstruction in logistics applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535935/
https://www.ncbi.nlm.nih.gov/pubmed/37765895
http://dx.doi.org/10.3390/s23187838
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