Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection

Abstract Previous studies have primarily focused on converting point clouds (PC) into a dense mech of 3D finite element models, neglecting the conversion of PCs into as-built wireframe models with two-node elements for line elements such as beams and columns. This study aims to demonstrate the feasibility of this direct conversion, utilizing building framing patterns to create wireframe models. The study also integrates the OpenSeesPy package for modal analysis and double integration for bending estimation to demonstrate the application of the presented method in robotic inspection. Results indicate the successful conversion of a 4-story mass timber building PC to a 3D structural model with an average error of 7.5% under simplified assumptions. Further, two complex mass timber shed PCs were tested, resulting in detailed wireframe models. According to resource monitoring, our method can process ∼593 points/second, mostly affected by the number of neighbors used in the first stage of sparse points removal. Lastly, our method detects beams, columns, ceilings (floors), and walls with their directions. This research can facilitate various structural modeling directly based on PC data for digital twinning and autonomous robotic inspection.

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Publication Details

Journal
Autonomous Intelligent Systems
Published
2024-11-28
DOI
https://doi.org/10.1007/s43684-024-00082-w
Citations
11
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
9.18
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article

Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection

Arvin Ebrahimkhanlou, Farzad Azizi Zade
11 citations
Autonomous Intelligent Systems
3D Surveying and Cultural Heritage
9.18
article

Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection

Arvin Ebrahimkhanlou, Farzad Azizi Zade
article en
11 citations

Abstract

Abstract Previous studies have primarily focused on converting point clouds (PC) into a dense mech of 3D finite element models, neglecting the conversion of PCs into as-built wireframe models with two-node elements for line elements such as beams and columns. This study aims to demonstrate the feasibility of this direct conversion, utilizing building framing patterns to create wireframe models. The study also integrates the OpenSeesPy package for modal analysis and double integration for bending estimation to demonstrate the application of the presented method in robotic inspection. Results indicate the successful conversion of a 4-story mass timber building PC to a 3D structural model with an average error of 7.5% under simplified assumptions. Further, two complex mass timber shed PCs were tested, resulting in detailed wireframe models. According to resource monitoring, our method can process ∼593 points/second, mostly affected by the number of neighbors used in the first stage of sparse points removal. Lastly, our method detects beams, columns, ceilings (floors), and walls with their directions. This research can facilitate various structural modeling directly based on PC data for digital twinning and autonomous robotic inspection.

Autonomous Intelligent SystemsVol. 4(1)
Drexel University (US), Ferdowsi University of Mashhad (IR)
Openalex Percentile: Top 2%
3D Surveying and Cultural Heritage
9.18
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