Semantic Optimal Robot Navigation Using Building Information on Construction Sites

Abstract

Semantic Optimal Robot Navigation Using Building Information on Construction Sites Sina Karimi, Rafael Gomes Braga, Ivanka Iordanova and David St-Onge Pages 57-64 (2021 Proceedings of the 38th ISARC, Dubai, UAE, ISBN 978-952-69524-1-3, ISSN 2413-5844) Abstract: 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. Keywords: BIM; IFC; Optimal Navigation; Semantic; Autonomous Robot; Path Planning DOI: https://doi.org/10.22260/ISARC2021/0010 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley