Stührenberg, JanJanStührenbergTandon, AdityaAdityaTandonSmarsly, KayKaySmarsly2026-01-142026-01-14202532nd International Workshop on Intelligent Computing in Engineering, EG-ICE 2025https://hdl.handle.net/11420/60816Building information modeling (BIM) models contain valuable information for mobile robots deployed to increase the efficiency of automated building inspections. To access the information, robots require accurate localization relative to BIM models. Since BIM models represent the "as-planned" rather than the "as-built" state, localization is challenging due to deviations between BIM models and the reality. In this paper, lidar inertial odometry (LIO) and BIM are coupled in the "LIO-BIM" framework for robust and accurate mobile robot localization and mapping relative to BIM models. LIO-BIM overlays the as-built map with BIM models, enabling automated progress monitoring. The framework is implemented and validated on the ConSLAM dataset, which includes periodically collected data from a 3D lidar, an inertial measurement unit, and a camera at a construction site. The validation tests show robust and accurate 3D localization and mapping relative to BIM models in real-time, enabling effective automated progress monitoring.enhttps://creativecommons.org/licenses/by/4.0/Technology::690: Building, ConstructionTechnology::629: Other Branches::629.8: Control and Feedback Control SystemsConference Paperhttps://doi.org/10.15480/882.1646810.17868/strath.0009322710.15480/882.16468Conference Paper