BIM-Informed Visual SLAM for Construction Monitoring
Asier Bikandi-Noya, Miguel Fernandez-Cortizas, Muhammad Shaheer, Ali Tourani, Holger Voos, Jose Luis Sanchez-Lopez
Abstract
Monitoring construction sites requires comparing the as-planned design with the as-built state in real time. Visual SLAM offers a lightweight solution but is prone to trajectory drift in construction environments due to repetitive layouts, textureless surfaces, and occlusions. We augment an existing visual SLAM system with structural priors from the Building Information Model (BIM), associating detected walls with their BIM counterparts and including these correspondences as geometric constraints in the back-end optimization. The system operates in real time and is validated on multiple real construction sites, achieving 25.23% average trajectory error reduction and 7.14% map accuracy improvement over state-of-the-art baselines, with demonstrated resilience to incomplete BIM data and as-planned/as-built discrepancies.