Algorithms for automated generation of navigation models from building information models to support indoor map-matching

• Developed algorithms for automated generation of navigation models from BIM models
• Addressed a limitation of existing algorithm that generates centerline-based network models
• Extracted boundary-representations from BIM models to generate metric-based navigation models
• Extracted geometry and topology from BIM models to generate grid-based navigation models
• Validated the generality of developed algorithms for automated generation of navigation models

Navigation models are explicit representations of geometrical and topological information of physical environments that can be utilized for map-matching of indoor positioning data. This research paper presents algorithms for automated generation of three different types of navigation models, namely, centerline-based network, metric-based and grid-based navigation models, for map-matching of indoor positioning data. The abovementioned navigation models have been generated in an automated fashion from Industry Foundation Classes (IFC)-based building information models (BIM). Specifically, we have 1) built on and targeted addressing limitations of existing algorithms that generate centerline-based network navigation models for polygonal shapes, 2) developed an approach to extract 2D geometry and topology from IFC-based BIM for creating metric-based navigation models, and 3) modified an existing algorithm to generate grid-based navigation models using geometry and topology extracted from BIM. The abovementioned three types of navigation models have been generated for six different testbeds with varying shape, size and density of spaces. We have validated the generality of the developed algorithms by evaluating the accuracy of geometrical and topological information contained within the three types of navigation models generated from testbeds with varying spatial characteristics.