A Benchmark Data Set for Data Association

Abstract

In this technical report we present a data set which can be used by researchers to test and compare their algorithms related to feature-based SLAM and in particular data association tasks. The data set covers a large path mostly through an indoor office environment with artificial and natural landmarks. It provides odometry and geometrical results from computer vision-based landmark detection, as well as raw images and camera calibration data. The artificial landmarks are white discs on the floor where the position relative to the robot is provided as measurement. The natural landmarks are vertical lines where only the bearing relative to the robot is provided and data association is remarkably difficult. This technical report provides full information about experimental setup, model and measurement functions. The focus of this data set is on data association and for comparison of different approaches we provide full ground truth by annotating all features.