Real-time, anchor-free node tracking using ultrawideband range and odometry data

This paper extends our prior work in node localization and tracking when using both range measurements and odometry data. In our approach both types of distance data are combined using multidimensional scaling, a well known method of producing sets of estimated coordinates from measured `dissimilarity´ values. In this extension, knowledge of the entire data set is no longer assumed, making node tracking possible in real time as computing resources allow. The new algorithm´s performance is demonstrated through simulations for various parameter values. We also present tracking results from real ultrawideband range and encoder data gathered from our CSOT mobile robot testbed. The results show compelling performance when benchmarked against the traditional extended Kalman filter.