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Structure-From-Motion in 3D Space Using 2D Lidars

This paper presents a novel structure-from-motion methodology using 2D lidars (Light Detection And Ranging). In 3D space, 2D lidars do not provide sufficient information for pose estimation. For this reason, additional sensors have been used along with the lidar measurement. In this paper, we use a...

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Detalles Bibliográficos
Autores principales: Choi, Dong-Geol, Bok, Yunsu, Kim, Jun-Sik, Shim, Inwook, Kweon, In So
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336074/
https://www.ncbi.nlm.nih.gov/pubmed/28165372
http://dx.doi.org/10.3390/s17020242
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author Choi, Dong-Geol
Bok, Yunsu
Kim, Jun-Sik
Shim, Inwook
Kweon, In So
author_facet Choi, Dong-Geol
Bok, Yunsu
Kim, Jun-Sik
Shim, Inwook
Kweon, In So
author_sort Choi, Dong-Geol
collection PubMed
description This paper presents a novel structure-from-motion methodology using 2D lidars (Light Detection And Ranging). In 3D space, 2D lidars do not provide sufficient information for pose estimation. For this reason, additional sensors have been used along with the lidar measurement. In this paper, we use a sensor system that consists of only 2D lidars, without any additional sensors. We propose a new method of estimating both the 6D pose of the system and the surrounding 3D structures. We compute the pose of the system using line segments of scan data and their corresponding planes. After discarding the outliers, both the pose and the 3D structures are refined via nonlinear optimization. Experiments with both synthetic and real data show the accuracy and robustness of the proposed method.
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spelling pubmed-53360742017-03-16 Structure-From-Motion in 3D Space Using 2D Lidars Choi, Dong-Geol Bok, Yunsu Kim, Jun-Sik Shim, Inwook Kweon, In So Sensors (Basel) Article This paper presents a novel structure-from-motion methodology using 2D lidars (Light Detection And Ranging). In 3D space, 2D lidars do not provide sufficient information for pose estimation. For this reason, additional sensors have been used along with the lidar measurement. In this paper, we use a sensor system that consists of only 2D lidars, without any additional sensors. We propose a new method of estimating both the 6D pose of the system and the surrounding 3D structures. We compute the pose of the system using line segments of scan data and their corresponding planes. After discarding the outliers, both the pose and the 3D structures are refined via nonlinear optimization. Experiments with both synthetic and real data show the accuracy and robustness of the proposed method. MDPI 2017-02-03 /pmc/articles/PMC5336074/ /pubmed/28165372 http://dx.doi.org/10.3390/s17020242 Text en © 2017 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Choi, Dong-Geol
Bok, Yunsu
Kim, Jun-Sik
Shim, Inwook
Kweon, In So
Structure-From-Motion in 3D Space Using 2D Lidars
title Structure-From-Motion in 3D Space Using 2D Lidars
title_full Structure-From-Motion in 3D Space Using 2D Lidars
title_fullStr Structure-From-Motion in 3D Space Using 2D Lidars
title_full_unstemmed Structure-From-Motion in 3D Space Using 2D Lidars
title_short Structure-From-Motion in 3D Space Using 2D Lidars
title_sort structure-from-motion in 3d space using 2d lidars
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336074/
https://www.ncbi.nlm.nih.gov/pubmed/28165372
http://dx.doi.org/10.3390/s17020242
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