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 feasi...
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| Format: | Article |
| Language: | English |
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Springer
2024-11-01
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| Series: | Autonomous Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s43684-024-00082-w |
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| _version_ | 1850107425794818048 |
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| author | Farzad Azizi Zade Arvin Ebrahimkhanlou |
| author_facet | Farzad Azizi Zade Arvin Ebrahimkhanlou |
| author_sort | Farzad Azizi Zade |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-f7aeb2c7d69d45b59da2af2f5cd70e62 |
| institution | OA Journals |
| issn | 2730-616X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Springer |
| record_format | Article |
| series | Autonomous Intelligent Systems |
| spelling | doaj-art-f7aeb2c7d69d45b59da2af2f5cd70e622025-08-20T02:38:35ZengSpringerAutonomous Intelligent Systems2730-616X2024-11-014112310.1007/s43684-024-00082-wPoint clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspectionFarzad Azizi Zade0Arvin Ebrahimkhanlou1Mechanical Engineering Department, Ferdowsi University of MashhadDepartment of Civil, Architectural and Environmental Engineering, Drexel UniversityAbstract 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.https://doi.org/10.1007/s43684-024-00082-wAutonomous robotic inspectionPoint Cloud to finite elementTwo-node WireframeModal analysisDigital twinBuilding Information Modeling |
| spellingShingle | Farzad Azizi Zade Arvin Ebrahimkhanlou Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection Autonomous Intelligent Systems Autonomous robotic inspection Point Cloud to finite element Two-node Wireframe Modal analysis Digital twin Building Information Modeling |
| title | Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection |
| title_full | Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection |
| title_fullStr | Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection |
| title_full_unstemmed | Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection |
| title_short | Point clouds to as-built two-node wireframe digital twin: a novel method to support autonomous robotic inspection |
| title_sort | point clouds to as built two node wireframe digital twin a novel method to support autonomous robotic inspection |
| topic | Autonomous robotic inspection Point Cloud to finite element Two-node Wireframe Modal analysis Digital twin Building Information Modeling |
| url | https://doi.org/10.1007/s43684-024-00082-w |
| work_keys_str_mv | AT farzadazizizade pointcloudstoasbuilttwonodewireframedigitaltwinanovelmethodtosupportautonomousroboticinspection AT arvinebrahimkhanlou pointcloudstoasbuilttwonodewireframedigitaltwinanovelmethodtosupportautonomousroboticinspection |