A reference system for indoor localization testbeds

We present a low-cost robot system capable of performing robust indoor localization while carrying components of another system which shall be evaluated. Using off-the-shelf components, the ground truth positioning data provided by the robot can be used to evaluate a variety of localization systems and algorithms. Not needing any pre-installed components in its environment, it is very easy to setup. The robot system relies on wheel-odometry data of a Roomba robot, and visual distance measurements of two Kinects. The Robot Operating System (ROS) is used for the localization process according to a precise pre-drawn floor plan that may be enhanced with Simultaneous Localization and Mapping (SLAM). The system is able to estimate its position with an average error of 6.7 cm. It records its own positioning data as well as the data from the system under evaluation and provides simple means for analysis. It is also able to re-drive a previous test run if reproducable conditions are needed.