Semantic Navigation Using Building Information on Construction Sites
This addresses the need for safer and more precise robot navigation in construction, though it appears incremental by applying existing BIM data to robotics.
The paper tackles the problem of enabling mobile robots to navigate construction sites more intelligently by leveraging Building Information Models (BIM) for semantic data, resulting in a system that allows non-experts to deploy robots and supports optimal path planning validated through experiments.
With the growth in automated data collection of construction projects, the need for semantic navigation of mobile robots is increasing. In this paper, we propose an infrastructure to leverage building-related information for smarter, safer and more precise robot navigation during construction phase. Our use of Building Information Models (BIM) in robot navigation is twofold: (1) the intuitive semantic information enables non-experts to deploy robots and (2) the semantic data exposed to the navigation system allows optimal path planning (not necessarily the shortest one). Our Building Information Robotic System (BIRS) uses Industry Foundation Classes (IFC) as the interoperable data format between BIM and the Robotic Operating System (ROS). BIRS generates topological and metric maps from BIM for ROS usage. An optimal path planer, integrating critical components for construction assessment is proposed using a cascade strategy (global versus local). The results are validated through series of experiments in construction sites.