Accurate indoor localization for RGB-D smartphones and tablets given 2D floor plans

Accurate localization in indoor environments is widely regarded as a key opener for various location-based services. Despite tremendous advancements in the development of innovative sensor concepts, the most effective and accurate solutions to this problem make use of a map computed from sensory data. In this paper, we present an efficient approach to localize an RGB-D smartphone or tablet that only makes use of a two-dimensional outline of the environment as a map as it is typically available from architectural drawings. Our technique employs a particle filter to estimate the 6DoF pose. We propose a sensor model that robustly estimates the likelihood of measurements and accommodates the disagreements between floor plans and real world data. In extensive experiments, we demonstrate that our approach is able to globally localize a user in a given 2D floor plan using a Google Tango device and to accurately track the user in such an environment.