TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. TUHH
  3. Publications
  4. LIO-BIM – Coupling lidar inertial odometry with building information modeling for robot localization and mapping
 
Options

LIO-BIM – Coupling lidar inertial odometry with building information modeling for robot localization and mapping

Citation Link: https://doi.org/10.15480/882.15254
Publikationstyp
Journal Article
Date Issued
2025-05-24
Sprache
English
Author(s)
Stührenberg, Jan  
Digitales und autonomes Bauen B-1  
Smarsly, Kay 
Digitales und autonomes Bauen B-1  
TORE-DOI
10.15480/882.15254
TORE-URI
https://hdl.handle.net/11420/55834
Journal
Advanced engineering informatics  
Volume
66
Article Number
103477
Citation
Advanced Engineering Informatics 66: 103477 (2025)
Publisher DOI
10.1016/j.aei.2025.103477
Scopus ID
2-s2.0-105005830936
Publisher
Elsevier
Mobile robots deployed to automate tasks in the construction industry require accurate robot localization and navigation. Building information modeling (BIM) is increasingly prevalent, and BIM models are interpretable by robots to help navigate in or around buildings. Most approaches towards robot localization through BIM models solely rely on maps derived from the BIM models requiring models with a high level of development (LOD) and the accurate modeling of non-structural objects. In practice, however, BIM models often employ a limited LOD and non-structural objects, if modeled, may appear in different locations, which may result in scan-BIM deviations and thus in localization errors. This paper presents the so called “LIO-BIM” framework, which couples lidar inertial odometry (LIO) and BIM for robust mobile robot localization and mapping, using 3D lidar to overcome the issues related to scan-BIM deviations. LIO-BIM builds upon simultaneous localization and mapping techniques and performs scan matching multiple times, i.e. (i) scan matching of the latest lidar scan with lidar scans previously recorded to maintain an accurate map of the environment, and (ii) scan matching of a local map around the robot with a BIM model to enable localization and mapping relative to the BIM model. The maps may be used at run-time, e.g., for construction progress monitoring or quality inspection. The framework, whose code is provided as open source, is implemented on a quadruped robot equipped with a 3D lidar, an inertial measurement unit, and a camera, and it is validated in a cluttered indoor office environment represented by a BIM model. Furthermore, the framework is validated on the ConSLAM dataset showcasing a cluttered construction site environment. As a result, the validation tests demonstrate accurate and robust 3D localization and mapping aligned with BIM models in real-time.
Subjects
Building information modeling | Construction inspection | Factor graphs | Quadruped robots | Scan matching | Simultaneous localization and mapping
DDC Class
620.1: Engineering Mechanics and Materials Science
624: Civil Engineering, Environmental Engineering
629.8: Control and Feedback Control Systems
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
Loading...
Thumbnail Image
Name

1-s2.0-S1474034625003702-main.pdf

Type

Main Article

Size

17.93 MB

Format

Adobe PDF

TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback