Robust Indoor Localization on a Commercial Smart Phone

Abstract

Low-cost localization solutions for indoor environments have a variety of real-world applications ranging from emergency evacuation to mobility aids for people with disabilities. In this paper, we introduce a methodology for indoor localization using a commercial smart-phone combining dead reckoning and Wifi signal strength fingerprinting. Additionally, we outline an automated procedure for collecting Wifi calibration data that uses a robot equipped with a laser rangefinder and fiber optic gyroscope. These measurements along with a generated robot map of the environment are combined using a particle filter towards robust pose estimation. The uniqueness of our approach lies in the implementation of the complementary nature of the solution as well as in the efficient adaptation to the smart-phone platform. The system was tested using multiple participants in two different indoor environments, and achieved localization accuracies on the order of 5 meters; sufficient for a variety of navigation and context-aware applications.