Scaffolds are essential temporary structures on construction sites. Since scaffolds are frequently installed and dismantled, the inspection needs to be performed in real-time. This paper proposes a framework to automate the acquisition process of scaffold point cloud data using a robot dog. First, a Simultaneous Localization and Mapping (SLAM) algorithm (LIO-SAM) is deployed for real-time map creation based on laser-based 3D data. Scaffolds are automatically detected using the bird's eye view (BEV) projection images of the registered 3D point clouds. A scanning distance is also determined for each detected scaffold to move the robot dog to an optimal location. The robot dog can successfully scan the scaffolds on construction sites by using the proposed framework.
|Title of host publication||Proceedings of the 39th International Symposium on Automation and Robotics in Construction, ISARC 2022|
|Publisher||International Association for Automation and Robotics in Construction (IAARC)|
|Number of pages||6|
|Publication status||Published - 2022|
|Event||39th International Symposium on Automation and Robotics in Construction, ISARC 2022 - Bogota, Colombia|
Duration: 2022 Jul 13 → 2022 Jul 15
|Name||Proceedings of the International Symposium on Automation and Robotics in Construction|
|Conference||39th International Symposium on Automation and Robotics in Construction, ISARC 2022|
|Period||22/7/13 → 22/7/15|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Education (No. 2018R1A6A1A08025348) and the "National R&D Project for Smart Construction Technology (No.22SMIP-A156488-03) funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation.
© 2022 International Association on Automation and Robotics in Construction.
All Science Journal Classification (ASJC) codes
- Building and Construction
- Civil and Structural Engineering
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality
- Artificial Intelligence
- Computer Science Applications