A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing

3D concrete printing (3DCP) has attracted significant attention due to the benefits of enhanced productivity and sustainability. However, existing 3DCP techniques face challenges of automation and practicality in integrating conventional rebar reinforcement with printed concrete structures. This stu...

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Main Authors: Du, Song, Teng, Fei, Zhuang, Zicheng, Zhang, Dong, Li, Mingyang, Li, Heng, Weng, Yiwei
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/178570
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1785702024-06-29T16:47:58Z A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing Du, Song Teng, Fei Zhuang, Zicheng Zhang, Dong Li, Mingyang Li, Heng Weng, Yiwei School of Mechanical and Aerospace Engineering Singapore Centre for 3D Printing Engineering 3D concrete printing Rebar reinforcement 3D concrete printing (3DCP) has attracted significant attention due to the benefits of enhanced productivity and sustainability. However, existing 3DCP techniques face challenges of automation and practicality in integrating conventional rebar reinforcement with printed concrete structures. This study presents an automated robot system coupled with Building Information Modeling (BIM) to address the challenge. Dynamo scripts in BIM were used to generate printing paths, further optimised by a proposed algorithm for incorporating rebar reinforcement. A deep learning model was adopted to identify rebars with large aspect ratios. The average accuracy of rebar recognition is 92.5%, with a position error within 2 mm. A centralised control system was developed for multiple-device communication, including a camera, a robot arm, and a gripper. Finally, a real-time demonstration was conducted, representing the first practical demonstration of an automated robotic system to integrate rebar reinforcement with printed structures using BIM-generated data in the physical world. Published version This work was supported by Department of Building and Real Estate, Hong Kong Polytechnic University: [Grant NumberP0038598]. 2024-06-26T06:06:53Z 2024-06-26T06:06:53Z 2024 Journal Article Du, S., Teng, F., Zhuang, Z., Zhang, D., Li, M., Li, H. & Weng, Y. (2024). A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing. Virtual and Physical Prototyping, 19(1), e2332423-. https://dx.doi.org/10.1080/17452759.2024.2332423 1745-2759 https://hdl.handle.net/10356/178570 10.1080/17452759.2024.2332423 2-s2.0-85188606568 1 19 e2332423 en Virtual and Physical Prototyping © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 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
3D concrete printing
Rebar reinforcement
spellingShingle Engineering
3D concrete printing
Rebar reinforcement
Du, Song
Teng, Fei
Zhuang, Zicheng
Zhang, Dong
Li, Mingyang
Li, Heng
Weng, Yiwei
A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing
description 3D concrete printing (3DCP) has attracted significant attention due to the benefits of enhanced productivity and sustainability. However, existing 3DCP techniques face challenges of automation and practicality in integrating conventional rebar reinforcement with printed concrete structures. This study presents an automated robot system coupled with Building Information Modeling (BIM) to address the challenge. Dynamo scripts in BIM were used to generate printing paths, further optimised by a proposed algorithm for incorporating rebar reinforcement. A deep learning model was adopted to identify rebars with large aspect ratios. The average accuracy of rebar recognition is 92.5%, with a position error within 2 mm. A centralised control system was developed for multiple-device communication, including a camera, a robot arm, and a gripper. Finally, a real-time demonstration was conducted, representing the first practical demonstration of an automated robotic system to integrate rebar reinforcement with printed structures using BIM-generated data in the physical world.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Du, Song
Teng, Fei
Zhuang, Zicheng
Zhang, Dong
Li, Mingyang
Li, Heng
Weng, Yiwei
format Article
author Du, Song
Teng, Fei
Zhuang, Zicheng
Zhang, Dong
Li, Mingyang
Li, Heng
Weng, Yiwei
author_sort Du, Song
title A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing
title_short A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing
title_full A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing
title_fullStr A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing
title_full_unstemmed A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing
title_sort bim-enabled robot control system for automated integration between rebar reinforcement and 3d concrete printing
publishDate 2024
url https://hdl.handle.net/10356/178570
_version_ 1814047104184614912