A Real-world Visual SLAM Dataset for Indoor Construction Sites

Wenyu LI, Xinyu CHEN, Yantao YU

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

Abstract

This paper presents a RGBD slam construction dataset with a mounted platform, designed to collect the
unique challenges encountered in construction sites. An Ouster OS0-128 LiDAR is utilized as the sensor of
LiDAR SLAM, working as the ground truth for localization. Our dataset records various construction settings
with different stages of building materials and structures, such as concrete, brick, plaster, and putty, providing a
comprehensive benchmark for training and evaluating SLAM algorithms. Through testing on current SLAM
algorithms, we demonstrate the limitations of traditional approaches in these environments and provide a VINS
based algorithm as the benchmark. This dataset serves as a valuable resource for researchers aiming to enhance
SLAM performance in the real construction environments. The detailed information of the dataset is available at
https://github.com/WenyuLWY/HCIC-Construction-VSLAM-Dataset.git
Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Civil and Building Engineering Infomatics
PublisherHong Kong University of Science and Technology
Pages289-296
Number of pages8
Publication statusAccepted/In press - 2025
EventThe 6th International Conference on Civil and Building Engineering Informatics (ICCBEI 2025) - , Hong Kong
Duration: 8 Jan 202511 Jan 2025

Conference

ConferenceThe 6th International Conference on Civil and Building Engineering Informatics (ICCBEI 2025)
Country/TerritoryHong Kong
Period8/01/2511/01/25

Keywords

  • Visual SLAM
  • Construction Robot
  • Dataset

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