Application of BIM + Layout Robot Technology in the Positioning of Curved Wall
- DOI
- 10.2991/978-94-6463-902-5_12How to use a DOI?
- Keywords
- BIM; Intelligent construction; Layout robot; Surface
- Abstract
The construction accuracy and efficiency of curved walls have become a critical challenge as building designs grow more complex. This study explores a positioning method for curved walls that integrates BIM technology with layout robots. By digitally constructing BIM models and converting high-precision data from layout robots, the method achieves automated and intelligent construction layout. Using the actual project case of Chongqing Fourth People’s Hospital, the study demonstrates that this technology can significantly reduce traditional measurement errors, improve positioning efficiency by over 30%, and lower labor costs. The results show that the integration of BIM and layout robots provides quantifiable and traceable technical support for the construction of complex curved surfaces, which is of practical significance for advancing intelligent construction.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Tao Wang AU - Ruiji Li AU - Shaoquan Zhang AU - Zhixin Liu AU - Yi Tu AU - Wei Jiang PY - 2025 DA - 2025/12/16 TI - Application of BIM + Layout Robot Technology in the Positioning of Curved Wall BT - Proceedings of the 2025 7th International Conference on Civil Engineering, Environment Resources and Energy Materials (CCESEM 2025) PB - Atlantis Press SP - 113 EP - 120 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-902-5_12 DO - 10.2991/978-94-6463-902-5_12 ID - Wang2025 ER -