Global BIM-point cloud registration and association for construction progress monitoring

Traditional manual and semi-automatic approaches rely heavily on surveying control points and manually picking equivalent point pairs, which is time-consuming and labor-intensive. This paper proposes an automatic algorithm for automatic global BIM-point registration and association to support construction progress monitoring. A representation using distance fields is proposed to efficiently integrate BIM in registration tasks. By leveraging a coarse-to-fine strategy, a primitive-level coarse algorithm is developed to achieve rough alignment between BIM and point cloud. This approach is then complemented by a point-level fine registration approach, which enables simultaneous pose refinement and BIM-point association. Extensive experiments are conducted on the data from simulation and real-world construction sites. The results demonstrate the promising registration and association performance of the proposed algorithm.