Localizing Tags Using Mobile Infrastructure

This paper presents algorithms, simulations, and empirical results of a system that finds relative tag positions in 3D space using a new approach called “mobile infrastructure.” Mobile infrastructure consists of one or more sensors in a fixed configuration on a mobile platform, and a set of tags affixed to objects or locations in the environment which the users want to localize. It is especially useful in cases where infrastructure is needed only temporarily, such as during installation, calibration, or maintenance. Mobile infrastructure can cover a much larger area than installed infrastructure with the same number of sensors, and is especially useful in cases where localization hardware costs are asymmetric, with expensive sensors and inexpensive tags. The data collected at various positions are combined by a simple “leapfrog” procedure, with constrained optimization to obtain better accuracy. Our system achieves about one foot (0.3 meter) accuracy with 90% confidence in indoor environments.