Cargando…

Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar

This paper attempts to uncover one possible method for the IMR (indoor mobile robot) to perform indoor exploration associated with SLAM (simultaneous localization and mapping) using LiDAR. Specifically, the IMR is required to construct a map when it has landed on an unexplored floor of a building. W...

Descripción completa

Detalles Bibliográficos
Autores principales: Ismail, Hasan, Roy, Rohit, Sheu, Long-Jye, Chieng, Wei-Hua, Tang, Li-Chuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878334/
https://www.ncbi.nlm.nih.gov/pubmed/35214588
http://dx.doi.org/10.3390/s22041689
_version_ 1784658636626198528
author Ismail, Hasan
Roy, Rohit
Sheu, Long-Jye
Chieng, Wei-Hua
Tang, Li-Chuan
author_facet Ismail, Hasan
Roy, Rohit
Sheu, Long-Jye
Chieng, Wei-Hua
Tang, Li-Chuan
author_sort Ismail, Hasan
collection PubMed
description This paper attempts to uncover one possible method for the IMR (indoor mobile robot) to perform indoor exploration associated with SLAM (simultaneous localization and mapping) using LiDAR. Specifically, the IMR is required to construct a map when it has landed on an unexplored floor of a building. We had implemented the e-SLAM (exploration-based SLAM) using the coordinate transformation and the navigation prediction techniques to achieve that purpose in the engineering school building which consists of many 100-m(2) labs, corridors, elevator waiting space and the lobby. We first derive the LiDAR mesh for the orthogonal walls and filter out the static furniture and dynamic humans in the same space as the IMR. Then, we define the LiDAR pose frame including the translation and rotation from the orthogonal walls. According to the MSC (most significant corner) obtained from the intersection of the orthogonal walls, we calculate the displacement of the IMR. The orientation of the IMR is calculated from the alignment of orthogonal walls in the consecutive LiDAR pose frames, which is also assisted by the LQE (linear quadratic estimation) method. All the computation can be done in a single processor machine in real-time. The e-SLAM technique leads to a potential for the in-house service robot to start operation without having pre-scan LiDAR maps, which can save the installation time of the service robot. In this study, we use only the LiDAR and compared our result with the IMU to verify the consistency between the two navigation sensors in the experiments. The scenario of the experiment consists of rooms, corridors, elevators, and the lobby, which is common to most office buildings.
format Online
Article
Text
id pubmed-8878334
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-88783342022-02-26 Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar Ismail, Hasan Roy, Rohit Sheu, Long-Jye Chieng, Wei-Hua Tang, Li-Chuan Sensors (Basel) Article This paper attempts to uncover one possible method for the IMR (indoor mobile robot) to perform indoor exploration associated with SLAM (simultaneous localization and mapping) using LiDAR. Specifically, the IMR is required to construct a map when it has landed on an unexplored floor of a building. We had implemented the e-SLAM (exploration-based SLAM) using the coordinate transformation and the navigation prediction techniques to achieve that purpose in the engineering school building which consists of many 100-m(2) labs, corridors, elevator waiting space and the lobby. We first derive the LiDAR mesh for the orthogonal walls and filter out the static furniture and dynamic humans in the same space as the IMR. Then, we define the LiDAR pose frame including the translation and rotation from the orthogonal walls. According to the MSC (most significant corner) obtained from the intersection of the orthogonal walls, we calculate the displacement of the IMR. The orientation of the IMR is calculated from the alignment of orthogonal walls in the consecutive LiDAR pose frames, which is also assisted by the LQE (linear quadratic estimation) method. All the computation can be done in a single processor machine in real-time. The e-SLAM technique leads to a potential for the in-house service robot to start operation without having pre-scan LiDAR maps, which can save the installation time of the service robot. In this study, we use only the LiDAR and compared our result with the IMU to verify the consistency between the two navigation sensors in the experiments. The scenario of the experiment consists of rooms, corridors, elevators, and the lobby, which is common to most office buildings. MDPI 2022-02-21 /pmc/articles/PMC8878334/ /pubmed/35214588 http://dx.doi.org/10.3390/s22041689 Text en © 2022 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
Ismail, Hasan
Roy, Rohit
Sheu, Long-Jye
Chieng, Wei-Hua
Tang, Li-Chuan
Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar
title Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar
title_full Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar
title_fullStr Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar
title_full_unstemmed Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar
title_short Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar
title_sort exploration-based slam (e-slam) for the indoor mobile robot using lidar
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878334/
https://www.ncbi.nlm.nih.gov/pubmed/35214588
http://dx.doi.org/10.3390/s22041689
work_keys_str_mv AT ismailhasan explorationbasedslameslamfortheindoormobilerobotusinglidar
AT royrohit explorationbasedslameslamfortheindoormobilerobotusinglidar
AT sheulongjye explorationbasedslameslamfortheindoormobilerobotusinglidar
AT chiengweihua explorationbasedslameslamfortheindoormobilerobotusinglidar
AT tanglichuan explorationbasedslameslamfortheindoormobilerobotusinglidar