Autonomous operation of a robot dog for point cloud data acquisition of scaffolds

D. Chung, S. Paik, J. Kim, H. Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 39th International Symposium on Automation and Robotics in Construction, ISARC 2022
PublisherInternational Association for Automation and Robotics in Construction (IAARC)
Pages93-98
Number of pages6
ISBN (Electronic)9789526952420
Publication statusPublished - 2022
Event39th International Symposium on Automation and Robotics in Construction, ISARC 2022 - Bogota, Colombia
Duration: 2022 Jul 132022 Jul 15

Publication series

NameProceedings of the International Symposium on Automation and Robotics in Construction
Volume2022-July
ISSN (Electronic)2413-5844

Conference

Conference39th International Symposium on Automation and Robotics in Construction, ISARC 2022
Country/TerritoryColombia
CityBogota
Period22/7/1322/7/15

Bibliographical note

Funding 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.

Publisher Copyright:
© 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

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