Proceedings of the 2022 European Conference on Computing in Construction


IFC-based generation of semantic obstacle maps for autonomous robotic systems

Muhammad Anas Gopee, Samuel A. Prieto, Borja García de Soto
S.M.A.R.T. Construction Research Group, New York University Abu Dhabi, United Arab Emirates

DOI: 10.35490/EC3.2022.161
Abstract: Autonomous Robotic Systems (ARSs) in the construction industry usually have to perform preliminary mapping of construction environments before deployment. For large and complex sites, this can be time-consuming. With Building Information Modeling (BIM), a lot of information is already available about sites. This study proposes a method to make that information available to ARSs to streamline autonomous tasks and remove the need for mapping. This is achieved by automatically generating semantic and color-coded obstacle maps from IFC files. The results are obstacle maps that can be used for autonomous navigation that remove the need for mapping.
Keywords: IFC, Obstacle Map, Autonomous Systems, Semantic Information

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