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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Automatic wall slant angle map generation using 3D point clouds

  • Kim, Jeongyun (Department of Civil and Environmental Engineering, KAIST) ;
  • Yun, Seungsang (Robotics Program, KAIST) ;
  • Jung, Minwoo (Department of Civil and Environmental Engineering, KAIST) ;
  • Kim, Ayoung (Department of Civil and Environmental Engineering, KAIST) ;
  • Cho, Younggun (Department of Robotics Engineering, Yeungnam University)
  • Received : 2021.03.10
  • Accepted : 2021.06.16
  • Published : 2021.08.01
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Abstract

Recently, quantitative and repetitive inspections of the old urban area were conducted because many structures exceed their designed lifetime. The health of a building can be validated from the condition of the outer wall, while the slant angle of the wall widely serves as an indicator of urban regeneration projects. Mostly, the inspector directly measures the inclination of the wall or partially uses 3D point measurements using a static light detection and ranging (LiDAR). These approaches are costly, time-consuming, and only limited space can be measured. Therefore, we propose a mobile mapping system and automatic slant map generation algorithm, configured to capture urban environments online. Additionally, we use the LiDAR-inertial mapping algorithm to construct raw point clouds with gravity information. The proposed method extracts walls from raw point clouds and measures the slant angle of walls accurately. The generated slant angle map is evaluated in indoor and outdoor environments, and the accuracy is compared with real tiltmeter measurements.

Keywords

Acknowledgement

This research was supported by the grant (21TSRD-B151228-03) from Urban Declining Area Regenerative Capacity-Enhancing Technology Research Program funded by Ministry of Land, Infrastructure, and Transport of Korean government.

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