Journal of the Korea Institute of Building Construction (한국건축시공학회지)

The Korean Institute of Building Construction (한국건축시공학회)
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Exploring the Combined Use of LiDAR and Augmented Reality for Enhanced Vertical and Horizontal Measurements of Structural Frames

골조 수직, 수평 측정작업 시 LiDAR 및 AR 기술 적용방안 제시

  • Received : 2023.03.10
  • Accepted : 2023.06.05
  • Published : 2023.06.20
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Abstract

This study is centered on the combined use of LiDAR(Light Detection and Ranging) and AR(Augmented Reality) technologies during vertical and horizontal frame measurements in construction projects. The intention is to enhance the quality control procedure, elevate accuracy, and curtail manual labor along with time expenditure. Present methods for accuracy inspection in frame construction often grapple with reliability concerns due to subjective interpretation and the scope for human error. This research recommends the application of LiDAR and AR technologies to counter these issues and augment the efficiency of the inspection process, along with facilitating the dissemination of results. The suggested technique involves the collection of 3D point cloud data of the frame utilizing LiDAR and leveraging this data for checks on construction accuracy. Furthermore, the inspection outcomes are fed into a BIM (Building Information Modeling) model, and the results are visualized via AR. Upon juxtaposing this methodology with the current approach, it is evident that it offers benefits in terms of objective inspection, speed, precise result sharing, and potential enhancements to the overall quality and productivity of construction projects.

건설프로젝트 진행 시 골조공사 후 시공상태를 점검하는 업무가 필수적이며, 이에 골조의 수직 및 수평 정확도를 점검하고 결함에 대한 보수작업을 수행한다. 하지만 기존의 업무방식은 점검자의 주관적 판단 및 인적오류의 발생 가능성으로 인한 신뢰성 문제, 수작업으로 인한 인력 및 시간 소모적 문제 등이 존재한다. 이에 본 연구는 상기 문제점을 해결하고, 골조공사 시공상태 점검 및 결과공유 과정의 효율을 높이고자 LiDAR 및 AR 기술의 활용방안을 제안하였다. 본 연구에서는 LiDAR를 통해 골조의 3D Point Cloud 데이터를 취득하여 시공상태 점검에 적용하는 방안과, 점검결과 데이터를 BIM 모델에 입력 후, AR을 통해 시각화하는 방안을 제안하였다. 이는 기존 방식 대비 점검과정의 객관성, 결과공유의 신속성 및 정확도 측면에서 효율적인 방식임을 확인하였으며, 더불어 건설프로젝트 전체의 품질 및 생산성 향상에 기여할수 있을 것으로 기대된다.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIT)(No.2020R1A2C1005263).

References

  1. Yoon S, Son S, Kim S. Construction, and curing integrated management of defects in finishing works of apartment buildings. Sustainability. 2021 May;13(10):5382. https://doi.org/10.3390/su13105382
  2. Wang J, Sun W, Shou W, Wang X, Wu C, Chong HY, Liu Y,Sun C. Integrating BIM and LiDAR for real-time construction quality control. Journal of Intelligent & Robotic Systems. 2015 Sep;79:417-32. https://doi.org/10.1007/s10846-014-0116-8
  3. Kim JY, Kim GH. Application of 3D laser scanning technology to the measurement of construction precision in building structural frame construction. Journal of the Architectural Institute of Korea. 2022 Apr;38(4):245-53. https://doi.org/10.5659/JAIK.2022.38.4.245
  4. Kim MK, Sohn H, Chang CC. Automated dimensional quality assessment of precast concrete panels using terrestrial laser scanning. Automation in construction. 2014 Sep;45:163-77. https://doi.org/10.1016/j.autcon.2014.05.015
  5. Kim MK, Sohn H, Chang CC. Localization and quantification of concrete spalling defects using terrestrial laser scanning. Journal of Computing in Civil Engineering. 2015 Nov;29(6):04014086. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000415
  6. Lee DU, Yun SH. Improvement of construction management process for the site manager in small scale building construction project. Journal of the Korea Institute of Building Construction. 2018 Feb;18(1):81-7. https://doi.org/10.5345/JKIBC.2018.18.1.081
  7. Gamba P, Houshmand B. Digital surface models and building extraction: A comparison of IFSAR and LIDAR data. IEEE Transactions on Geoscience and Remote Sensing. 2000 Jul;38(4):1959-68. https://doi.org/10.1109/36.851777
  8. Liu J, Xu D, Hyyppa J, Liang Y. A survey of applications with combined BIM and 3D laser scanning in the life cycle of buildings. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021 Jan;14:5627-37. https://doi.org/10.1109/JSTARS.2021.3068796
  9. Tan Y, Li S, Wang Q. Automated geometric quality inspection of prefabricated housing units using BIM and LiDAR. Remote Sensing. 2020 Aug;12(15):2492. https://doi.org/10.3390/rs12152492
  10. Wang SK, Chen HM. A construction progress on-site monitoring and presentation system based on the integration of augmented reality and BIM. 2020 Proceedings of the 37th ISARC; 2020 Oct 27-28; Kitakyushu, Japan. Waterloo (IA): The International Association for Automation and Robotics in Construction; 2020. p. 147-54.
  11. Song J, Yu J, Kim K. On-site quality control support tools based on mobile BIM:focusing on quality management work. Korean Journal of Construction Engineering and Management. 2020 Nov;21(6):27-37. https://doi.org/10.6106/KJCEM.2020.21.6.027
  12. Mora R, Martin-Jimenez J A, Laguela S, Gonzalez-Aguilera D. Automatic point-cloud registration for quality control in building works. Applied Sciences. 2021 Feb;11(4):1465. https://doi.org/10.3390/app11041465
  13. Pica D, Abanda FH. Emerging BIM-3d-laser scanning integration in construction practice. Proceedings of the 11th International Conference on Construction in the 21st Century; 2019 Sep 9-11; London, United Kingdom. London (United Kingdom): Springer International Publishing; 2021. p. 345-50.
  14. Lee DS, Kim GH. Smart quality inspection scheme for construction project using 3d scanning technology. Journal of the Korea Institute of Building Construction. 2020 Apr;20(2):191-8. https://doi.org/10.5345/JKIBC.2020.20.2.191
  15. Lin YC, Chang JX, Su YC. Developing construction defect management system using BIM technology in quality inspection. Journal of civil engineering and management. 2016 Jul;22(7):903-14. https://doi.org/10.3846/13923730.2014.928362
  16. Ma Z, Cai S, Mao N, Yang Q, Feng J, Wang P. Construction quality management based on a collaborative system using BIM and indoor positioning. Automation in Construction. 2018 Aug;92:35-45. https://doi.org/10.1016/j.autcon.2018.03.027
  17. Bassier M, Vincke S, De Winter H, Vergauwen M. Drift invariant metric quality control of construction sites using BIM and point cloud data. ISPRS International Journal of Geo-Information. 2020 Sep;9(9):545. https://doi.org/10.3390/ijgi9090545
  18. Park CS, Lee DY, Kwon OS, Wang X. A framework for proactive construction defect management using BIM, augmented reality and ontology-based data collection template. Automation in construction. 2013 Aug;33:61-71. https://doi.org/10.1016/j.autcon.2012.09.010
  19. Schiavi B, Havard V, Beddiar K, Baudry D. BIM data flow architecture with AR/VR technologies: Use cases in architecture, engineering and construction. Automation in Construction. 2022 Feb;134:104054. https://doi.org/10.1016/j.autcon.2021.104054
  20. Sangiorgio V, Martiradonna S, Fatiguso F, Lombillo I. Augmented reality based-decision making (AR-DM) to support multi-criteria analysis in constructions. Automation in construction. 2021 Apr;124:103567. https://doi.org/10.1016/j.autcon.2021.103567
  21. Chen K, Yang J, Cheng JC, Chen W, Li CT. Transfer learning enhanced AR spatial registration for facility maintenance management. Automation in Construction. 2020 May;113:103135. https://doi.org/10.1016/j.autcon.2020.103135
  22. Song Y, Koeck R, Luo S. Review and analysis of augmented reality (AR) literature for digital fabrication in architecture. Automation in Construction. 2021 Aug;128:103762. https://doi.org/10.1016/j.autcon.2021.103762
  23. Li X, Yi W, Chi HL, Wang X, Chan AP. A critical review of virtual and augmented reality (VR/AR) applications in construction safety. Automation in Construction. 2018 Feb;86:150-62. https://doi.org/10.1016/j.autcon.2017.11.003 
  24. Tsai LT, Chi HL, Wu TH, Kang SC. AR-based automatic pipeline planning coordination for on-site mechanical, electrical and plumbing system conflict resolution. Automation in Construction. 2022 Sep;141:104400. https://doi.org/10.1016/j.autcon.2022.104400
  25. Ratajczak J, Riedl M, Matt DT. BIM-based and AR application combined with location-based management system for the improvement of the construction performance. Buildings. 2019 May;9(5):118. https://doi.org/10.3390/buildings9050118
  26. Wang P, Wu P, Wang J, Chi HL, Wang X. A critical review of the use of virtual reality in construction engineering education and training. International journal of environmental research and public health. 2018 Jun;15(6):1204. https://doi.org/10.3390/ijerph15061204
  27. Garbett J, Hartley T, Heesom D. A multi-user collaborative BIM-AR system to support design and construction. Automation in Construction. 2021 Feb;122:103487. https://doi.org/10.1016/j.autcon.2020.103487
  28. Huang Z. Application research on BIM+ AR technology in construction safety management. In Journal of physics: conference series. 2020 Oct;1648(4):042019. https://doi.org/10.1088/1742-6596/1648/4/042019
  29. Yang L, Cheng JC, Wang Q. Semi-automated generation of parametric BIM for steel structures based on terrestrial laser scanning data. Automation in Construction. 2020 Apr;112:103037. https://doi.org/10.1016/j.autcon.2019.103037
  30. Turkan Y, Hong J, Laflamme S, Puri N. Adaptive wavelet neural network for terrestrial laser scanner-based crack detection. Automation in construction. 2018 Oct;94:191-202. https://doi.org/10.1016/j.autcon.2018.06.017
  31. Kim SH. 3D point cloud and 4D BIM-based construction project EV tracking process [dissertation]. [Gyeongsan (Korea)]: Yeungnam University; 2019. 205 p.
  32. Olanrewaju OI, Kineber AF, Chileshe N, Edwards DJ. Modelling the relationship between Building Information Modelling (BIM) implementation barriers, usage and awareness on building project lifecycle. Building and Environment. 2022 Jan;207:108556. https://doi.org/10.1016/j.buildenv.2021.108556
  33. Esfahani ME, Rausch C, Sharif MM, Chen Q, Haas C, Adey BT. Quantitative investigation on the accuracy and precision of Scan-to-BIM under different modelling scenarios. Automation in Construction. 2021 Jun;126:103686. https://doi.org/10.1016/j.autcon.2021.103686
  34. Weng Y, Mohamed NAN, Lee BJS, Gan NJH, Li M, Jen Tan M, Li H, Qian S. Extracting BIM information for lattice toolpath planning in digital concrete printing with developed dynamo script: a case study. Journal of Computing in Civil Engineering. 2021 May;35(3):05021001. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000964
  35. Sheikhkhoshkar M, Rahimian FP, Kaveh MH, Hosseini MR, Edwards DJ. Automated planning of concrete joint layouts with 4D-BIM. Automation in construction. 2019 Nov;107:102943. https://doi.org/10.1016/j.autcon.2019.102943
  36. Wang YG, He XJ, He J, Fan C. Virtual trial assembly of steel structure based on BIM platform. Automation in Construction. 2022 Sep;141:104395. https://doi.org/10.1016/j.autcon.2022.104395
  37. Meza S, Turk Z, Dolenc M. Measuring the potential of augmented reality in civil engineering. Advances in engineering software. 2015 Sep;90:1-10. https://doi.org/10.1016/j.advengsoft.2015.06.005