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Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels
This paper presents a fully original algorithm of graph SLAM developed for multiple environments—in particular, for tunnel applications where the paucity of features and the difficult distinction between different positions in the environment is a problem to be solved. This algorithm is modular, gen...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399184/ https://www.ncbi.nlm.nih.gov/pubmed/34450782 http://dx.doi.org/10.3390/s21165340 |
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author | Prados Sesmero, Carlos Villanueva Lorente, Sergio Di Castro, Mario |
author_facet | Prados Sesmero, Carlos Villanueva Lorente, Sergio Di Castro, Mario |
author_sort | Prados Sesmero, Carlos |
collection | PubMed |
description | This paper presents a fully original algorithm of graph SLAM developed for multiple environments—in particular, for tunnel applications where the paucity of features and the difficult distinction between different positions in the environment is a problem to be solved. This algorithm is modular, generic, and expandable to all types of sensors based on point clouds generation. The algorithm may be used for environmental reconstruction to generate precise models of the surroundings. The structure of the algorithm includes three main modules. One module estimates the initial position of the sensor or the robot, while another improves the previous estimation using point clouds. The last module generates an over-constraint graph that includes the point clouds, the sensor or the robot trajectory, as well as the relation between positions in the trajectory and the loop closures. |
format | Online Article Text |
id | pubmed-8399184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83991842021-08-29 Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels Prados Sesmero, Carlos Villanueva Lorente, Sergio Di Castro, Mario Sensors (Basel) Communication This paper presents a fully original algorithm of graph SLAM developed for multiple environments—in particular, for tunnel applications where the paucity of features and the difficult distinction between different positions in the environment is a problem to be solved. This algorithm is modular, generic, and expandable to all types of sensors based on point clouds generation. The algorithm may be used for environmental reconstruction to generate precise models of the surroundings. The structure of the algorithm includes three main modules. One module estimates the initial position of the sensor or the robot, while another improves the previous estimation using point clouds. The last module generates an over-constraint graph that includes the point clouds, the sensor or the robot trajectory, as well as the relation between positions in the trajectory and the loop closures. MDPI 2021-08-07 /pmc/articles/PMC8399184/ /pubmed/34450782 http://dx.doi.org/10.3390/s21165340 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 | Communication Prados Sesmero, Carlos Villanueva Lorente, Sergio Di Castro, Mario Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels |
title | Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels |
title_full | Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels |
title_fullStr | Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels |
title_full_unstemmed | Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels |
title_short | Graph SLAM Built over Point Clouds Matching for Robot Localization in Tunnels |
title_sort | graph slam built over point clouds matching for robot localization in tunnels |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399184/ https://www.ncbi.nlm.nih.gov/pubmed/34450782 http://dx.doi.org/10.3390/s21165340 |
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