Integrating Robot Mapping and Augmented Building Simulation

Abstract

This paper discusses a framework for integrated augmented reality (AR) architecture for indoor thermal performance data visualization that utilizes a mobile robot to generate environment maps. It consists of three modules: robot mapping, computational fluid dynamics (CFD) simulation, and AR visualization. The robot mapping module enables the modeling of spatial geometry using a mobile robot. In order to generate steady approximations to scanned three-dimensional data sets, the paper presents a novel “split-and-merge expectation-maximization patch fitting” (SMEMPF) planar approximation method. It allows for precise adjustment of patches independent from the initial model. The final result is a set of patches identifying planar macrostructures that consist of a collection of supported tiles. These patches are used to model the spatial geometry under investigation. The CFD simulation module facilitates the prediction of building performance databased on the spatial data generated using the SMEMPF method. The AR visualization module assists in interactive and immersive visualization of CFD simulation results. Such an integrated AR architecture will facilitate rapid multiroom mobile AR visualizations.