4.7 Article

Automated shape and pose updating of building information model elements from 3D point clouds

期刊

AUTOMATION IN CONSTRUCTION
卷 124, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.autcon.2021.103561

关键词

As-built BIM; Metaheuristics; Digital twin; Parameterization; Genetic algorithm; Simulated annealing; Non-rigid registration; Proto-BIM

资金

  1. Natural Sciences and Engineering Research Council of Canada (NSERC) [CGSD3 - 516799 -2018]
  2. Mitacs Accelerate
  3. Edge Architects [53162-10151]

向作者/读者索取更多资源

This paper introduces an approach for creating geometric agency within BIMs by leveraging their parametric capabilities, the accuracy of 3D point clouds, and the dexterity of metaheuristics, resulting in a dynamic BIM capable of updating its geometry to match a 3D point cloud. A case study demonstrates a significant reduction in average error between a BIM and the as-built conditions, providing a way to progressively capture accurate as-built conditions in BIM and predict potential assembly conflicts.
Generating an up-to-date BIM that accurately reflects as-built conditions is becoming necessary for ensuring fit between assemblies and construction sites. If an initial BIM (proto-BIM) could be automatically updated to reflect as-built conditions by changing shape and pose of BIM elements, it would be preferable over scan-to-BIM in many instances. An approach is presented herein for creating geometric agency within BIMs by exploiting their parametric capabilities, the accuracy of 3D point clouds, and the dexterity of metaheuristics. The result is a dynamic BIM (dyna-BIM) capable of updating its geometry to match a 3D point cloud. A case study for cast-in place concrete footings shows how the average error between a BIM and the as-built conditions can be reduced from 50.4 mm to 5.69 mm. This paper provides a way to progressively capture accurate as-built conditions in BIM and predict potential assembly conflicts, while maintaining the initial semantics and fidelity of an as designed BIM.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据