Journal of the Korea Institute of Building Construction (한국건축시공학회지)

The Korean Institute of Building Construction (한국건축시공학회)
권호 표지
DOI QR코드

DOI QR Code

Measuring Rebar Position Error and Marking Work for Automated Layout Robot Using LiDAR Sensor

마킹 로봇의 자동화를 위한 LiDAR 센서 기반 철근배근 오차 측정 및 먹매김 수행 프로세스 연구

  • Kim, Taehoon (Department of Architectural Engineering, Chosun University) ;
  • Lim, Hyunsu (Department of Architecture, Soonchunhyang University) ;
  • Cho, Kyuman (Department of Architectural Engineering, Chosun University)
  • Received : 2022.12.20
  • Accepted : 2023.01.16
  • Published : 2023.04.20
Download PDF
⟨ Previous Next ⟩

Abstract

Ensuring accuracy within tolerance is crucial for a marking robot; however, rebar displacement frequently occurs during the structural work process, necessitating corrections to layout lines or rebar locations. To guarantee precision and automation, the marking robot must be capable of measuring rebar error and determining appropriate adjustments for marking lines and rebar placement. Consequently, this study proposes a method for measuring rebar location error using a LiDAR sensor and implementing a layout assessment process based on the measurement results. The rebar recognition experiment using the LiDAR sensor yielded an average error of 5mm, demonstrating a reliable level of accuracy for wall rebars. Additionally, this research proposed a process that enables the robot to evaluate rebar and marking corrections based on the error range. The findings of this study can contribute to the automated operation of marking robots while accounting for construction errors, potentially leading to improvements in structural quality.

먹매김 로봇은 허용오차 이내의 정밀도를 확보하는 것이 매우 중요하다. 그러나 골조공사는 시공과정에서 철근배근의 변위가 빈번하게 발생하며, 해당오차는 먹선이나 철근위치의 수정을 요구한다. 먹매김 로봇은 정밀도 확보 및 자동화를 위해 철근의 오차를 측정하고 먹선과 철근의 수정을 스스로 판단할 수 있어야 한다. 이에 본 연구는 LiDAR 센서를 통한 철근배근의 오차 측정방안과 이를 바탕으로 먹매김 판단 프로세스를 제시하였다. LiDAR 센서를 활용한 철근인식 실험결과 평균적으로 5mm 내외의 오차를 발생하였으며, 이는 일반적으로 벽체에 적용되는 철근 수준에서 인식을 신뢰할만한 수준으로 나타났다. 또한 철근오차를 범위별로 판단하여 철근의 보정여부와 먹매김의 수행여부를 로봇이 스스로 판단할 수 있는 프로세스를 제시하였다. 본 연구결과는 시공오차를 고려한 먹매김로봇의 자동운영에 기여할 수 있으며 이를 통해 골조품질을 향상시킬 수 있을 것으로 기대된다.

Keywords

Acknowledgement

This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport(Grant 21CTAP-C163790-01) and by research fund from Chosun University, 2022.

References

  1. Kim TH, Lim HS, Cho KM. Conceptual robot design for the automated layout of building structures by integrating QFD and TRIZ. The International Journal of Advanced Manufacturing Technology. 2022 May;120:1793-804. https://doi.org/10.1007/s00170-022-08803-2
  2. Brosque C, Skeie G, Orn J, Jacobson J, Lau T, Fischer M. Comparison of construction robots and traditional methods for drilling, drywall, and layout tasks. 2020 International congress on human-computer interaction, optimization and robotic applications (HORA). 2020 Jun 26-28; Ankara, Turkey. Artvin (Turkey): Artvin Coruh University and IEEE Turkey Section; 2020. p. 1-14. https://doi.org/10.1109/HORA49412.2020.9152871
  3. Takehiro T, Kazuyuki M, Mikita M. Improvement of automated mobile marking robot system using reflectorless three-dimensional measuring instrument. 36th International Symposium on Automation and Robotics in Construction. 2019 May 21-24; Banff, Canada. Edinburgh (United Kingdom): The International Association for Automation and Robotics in Construction; 2019. p. 756-63. https://doi.org/10.22260/ISARC2019/0102
  4. Takashi K, Kouji S, Joji O. Marking robot in cooperation with three-dimensional measuring instruments. 35th International Symposium on Automation and Robotics in Construction. 2018 Jul 20-25; Berlin, Germany. Edinburgh (United Kingdom): The International Association for Automation and Robotics in Construction; 2018. p. 292-9. https://doi.org/10.22260/ISARC2018/0042
  5. Lim HS, Cho KM, Kim, TH. Development directions for automated layout system of building structures. Journal of The Korea Institute of Building Construction. 2021 Oct;21(5):387-96. https://doi.org/10.5345/JKIBC.2021.21.5.387
  6. Construction guidelines for rebar work [Internet]. Goyang (Korea): Korea Institute of Civil Engineering and Building Technology; 2022 Nov 21. Available from: https://www.codil.or.kr/viewDtlConWrkDtlSch.do?gubun=tch&pMetaCode=CIGCEI210162
  7. KDS 14 20 50: Design Criteria for Rebar Details of Concrete Structures [Internet]. Sejong (Korea): Ministry of Land, Infrastructure and Transport; 2022 Nov 21. Available from: https://www.kcsc.re.kr/StandardCode/Viewer/41005
  8. Ministry of Land, Infrastructure and Transport. Enforcement regulation of building act [Internet]. Seoul (Korea): Korea Law Information Center; 2022 Nov 21. Available from: https://www.law.go.kr/LSW/lsInfoP.do?efYd=20220211&lsiSeq=240383#J14934155
  9. Masri EE, Waters T, Ferguson N. Guided wave inspection of bars in reinforced-concrete beams using surface-mounted vibration sensors. Vibration. 2020 Sep;3(4):343-56. https://doi.org/10.3390/vibration3040023
  10. Jin J, Zhang W, Li F, Li M, Shi Y, Guo Z, Huang Q. Robotic binding of rebar based on active perception and planning. Automation in Construction. 2021 Dec;132:103939. https://doi.org/10.1016/j.autcon.2021.103939
  11. Kim MK, Thedja JPP, Wang Q. Automated dimensional quality assessment for formwork and rebar of reinforced concrete components using 3D point cloud data. Automation in Construction. 2020 Apr;112:103077. https://doi.org/10.1016/j.autcon.2020.103077
  12. Lim H, Kim T, Cho K, Kim T, Kim CW. An algorithm of making line correction for robot-based layout automation of building structures. Proccedings of the 9th International Conference on Construction Engineering and Project Management; 2022 Jun 20-23; Las Vegas, USA. Las Vegas (USA): the ICCEPM 2022 Organizaing Committee; 2022. p. 312-8.
  13. RPLIDAR A2: Key Parameters [Internet]. Shanghai (China): Shanghai Slamtec Co., Ltd.; 2022 Mar 18: Available from: https://www.slamtec.com/en/Lidar/A2Spec
  14. 2D-LiDAR sensor: TiM [Internet]. Seoul (Korea): Sick Korea; 2022 Apr 22: Available from: https://www.sick.com/kr/ko/products-by-tasks/position-determination/position-determination/2d-lidar-/tim/c/g570093