Stührenberg, JanJanStührenbergSmarsly, KayKaySmarsly2025-06-122025-06-122025-05-24Advanced Engineering Informatics 66: 103477 (2025)https://hdl.handle.net/11420/55834Mobile 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.en1474-03462025Elsevierhttps://creativecommons.org/licenses/by/4.0/Building information modeling | Construction inspection | Factor graphs | Quadruped robots | Scan matching | Simultaneous localization and mappingTechnology::620: Engineering::620.1: Engineering Mechanics and Materials ScienceTechnology::624: Civil Engineering, Environmental EngineeringTechnology::629: Other Branches::629.8: Control and Feedback Control SystemsJournal Articlehttps://doi.org/10.15480/882.1525410.1016/j.aei.2025.10347710.15480/882.15254Journal Article