A ros driven platform for radiomap management optimization in fingerprinting based indoor positioning

Abstract

An electromagnetic beacons infrastructure is commonly used in positioning applications within buildings where the GPS signal is not present. Through techniques of multilateration and fingerprinting an average accuracy of about 2 m can be reached, but the accuracy is limited by multiple reflections, obstacles and signal dispersion that make it unreliable analytic field modeling. Dense field sampling field allows a reconstruction more detailed but is costly and clever uneven sampling is appropriate. This work describes the progress of an interactive robotic platform under development to support field modeling and beacons positioning, through intelligent iterative strategies of data acquisition. The platform integrates a Matlab-based control system and simulation software: a robot equipped with distance sensors, able to perform autonomous navigation in a known environment, and a data logger module hosted in an Android mobile device, all connected via a ROS framework. Robot assisted field sampling is here proposed and used to reduce costs of radiomap construction and update. In particular, this technology is suitable for complex environments as museums and exhibitions.