A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing
| Title: | A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing |
|---|---|
| Authors: | Song Du, Fei Teng, Zicheng Zhuang, Dong Zhang, Mingyang Li, Heng Li, Yiwei Weng |
| Source: | Virtual and Physical Prototyping, Vol 19, Iss 1 (2024) |
| Publisher Information: | Taylor & Francis Group, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Science LCC:Manufactures |
| Subject Terms: | 3D concrete printing, rebar reinforcement, robot control system, deep learning, Building Information Modeling, Science, Manufactures, TS1-2301 |
| More Details: | ABSTRACT3D 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. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 17452759 1745-2767 1745-2759 |
| Relation: | https://doaj.org/toc/1745-2759; https://doaj.org/toc/1745-2767 |
| DOI: | 10.1080/17452759.2024.2332423 |
| Access URL: | https://doaj.org/article/41e2d2fbe2a547779e2bbdaf5f57734c |
| Accession Number: | edsdoj.41e2d2fbe2a547779e2bbdaf5f57734c |
| Database: | Directory of Open Access Journals |
| ISSN: | 17452759 17452767 |
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| DOI: | 10.1080/17452759.2024.2332423 |
| Published in: | Virtual and Physical Prototyping |
| Language: | English |