BIMBot for autonomous laser scanning in built environments
Accurate and complete 3D point clouds are essential in creating as-built building information modeling (BIM) models, although there are challenges in automating the process for 3D point cloud creation in complex environments. In this paper, an autonomous scanning system named BIMBot is introduced, w...
Saved in:
Main Authors: | , , , , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/174868 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-174868 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1748682024-04-20T16:49:42Z BIMBot for autonomous laser scanning in built environments Liang, Nanying Ang, Yu Pin Yeo, Kaiyun Wu, Xiao Xie, Yuan Cai, Yiyu School of Mechanical and Aerospace Engineering School of Computer Science and Engineering Engineering Autoscanning system Next best view Accurate and complete 3D point clouds are essential in creating as-built building information modeling (BIM) models, although there are challenges in automating the process for 3D point cloud creation in complex environments. In this paper, an autonomous scanning system named BIMBot is introduced, which integrates advanced light detection and ranging (LiDAR) technology with robotics to create 3D point clouds. Using our specially developed algorithmic pipeline for point cloud processing, iterative registration refinement, and next best view (NBV) calculation, this system facilitates an efficient, accurate, and fully autonomous scanning process. The BIMBot’s performance was validated using a case study in a campus laboratory, featuring complex structural and mechanical, electrical, and plumbing (MEP) elements. The experimental results showed that the autonomous scanning system produced 3D point cloud mappings in fewer scans than the manual method while maintaining comparable detail and accuracy, demonstrating its potential for wider application in complex built environments. Agency for Science, Technology and Research (A*STAR) Published version This research was funded by the RIE2020 Industry Alignment Fund–Industry Collaboration Projects (IAF–ICP) Funding Initiative, as well as cash-in-kind contributions from Surbana Jurong Pte Ltd., Singapore. 2024-04-15T01:56:02Z 2024-04-15T01:56:02Z 2024 Journal Article Liang, N., Ang, Y. P., Yeo, K., Wu, X., Xie, Y. & Cai, Y. (2024). BIMBot for autonomous laser scanning in built environments. Robotics, 13(2), 13020022-. https://dx.doi.org/10.3390/robotics13020022 2218-6581 https://hdl.handle.net/10356/174868 10.3390/robotics13020022 2-s2.0-85185958373 2 13 13020022 en Robotics © 2024 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 (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering Autoscanning system Next best view |
spellingShingle |
Engineering Autoscanning system Next best view Liang, Nanying Ang, Yu Pin Yeo, Kaiyun Wu, Xiao Xie, Yuan Cai, Yiyu BIMBot for autonomous laser scanning in built environments |
description |
Accurate and complete 3D point clouds are essential in creating as-built building information modeling (BIM) models, although there are challenges in automating the process for 3D point cloud creation in complex environments. In this paper, an autonomous scanning system named BIMBot is introduced, which integrates advanced light detection and ranging (LiDAR) technology with robotics to create 3D point clouds. Using our specially developed algorithmic pipeline for point cloud processing, iterative registration refinement, and next best view (NBV) calculation, this system facilitates an efficient, accurate, and fully autonomous scanning process. The BIMBot’s performance was validated using a case study in a campus laboratory, featuring complex structural and mechanical, electrical, and plumbing (MEP) elements. The experimental results showed that the autonomous scanning system produced 3D point cloud mappings in fewer scans than the manual method while maintaining comparable detail and accuracy, demonstrating its potential for wider application in complex built environments. |
author2 |
School of Mechanical and Aerospace Engineering |
author_facet |
School of Mechanical and Aerospace Engineering Liang, Nanying Ang, Yu Pin Yeo, Kaiyun Wu, Xiao Xie, Yuan Cai, Yiyu |
format |
Article |
author |
Liang, Nanying Ang, Yu Pin Yeo, Kaiyun Wu, Xiao Xie, Yuan Cai, Yiyu |
author_sort |
Liang, Nanying |
title |
BIMBot for autonomous laser scanning in built environments |
title_short |
BIMBot for autonomous laser scanning in built environments |
title_full |
BIMBot for autonomous laser scanning in built environments |
title_fullStr |
BIMBot for autonomous laser scanning in built environments |
title_full_unstemmed |
BIMBot for autonomous laser scanning in built environments |
title_sort |
bimbot for autonomous laser scanning in built environments |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/174868 |
_version_ |
1800916299099930624 |