Explore hidden information for indoor floor plan construction

The lack of digital floor plans in most buildings has become a huge obstacle to pervasive indoor location based services (LBS). Recently there has been quite some research that leverages various sensing data such as inertial, WiFi and images from ubiquitous mobile devices (e.g., smartphones) to construct floor plans at large scale and low costs. Although great efforts are made to improve the accuracy and robustness against sensing data errors and noises, the quality of reconstructed maps is still limited. In this paper, we explore the hidden geometric structure information of indoor environments, such as collinearity of doors along hallways, right-angle corners, and polygon/circular shapes of rooms to optimize floor plans. Such prior knowledge about building structures provide new spatial relationships among floor plan elements. Thus we can further improve the quality of reconstructed maps. Real experiments in two large buildings show that 90-percentile landmark location errors are reduced by more than 50% to within 1m, and most orientation errors are corrected. The overall shape of the map has become much closer to the ground truth as well.