Home/A Robust Method of Localization and Mapping Using Only Range

A Robust Method of Localization and Mapping Using Only Range

Joseph Djugash and Sanjiv Singh
Conference Paper, Carnegie Mellon University, International Symposium on Experimental Robotics, July, 2008

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

In this paper we present results in mobile robot localization and simultaneous localization and mapping (SLAM) using range from radio. In previous work we have shown how range readings from radio tags placed in the environment can be used to localize a robot and map tag locations using a standard extended Kalman filter (EKF) that linearizes the probability distribution due to range measurements based on prior estimates. Our experience with this method was that the filter could perform poorly and even diverge in cases of missing data and poor initialization. Here we present a new formulation that gains robustness without sacrificing accuracy. Specifically, our method is shown to have significantly better performance with poor and even no initialization, infrequent measurements, and incorrect data association. We present results from a mobile robot equipped with high accuracy ground truth, operating over several kilometers.

BibTeX Reference
@conference{Djugash-2008-10033,
title = {A Robust Method of Localization and Mapping Using Only Range},
author = {Joseph Djugash and Sanjiv Singh},
booktitle = {International Symposium on Experimental Robotics},
keyword = {Range-only, SLAM},
school = {Robotics Institute , Carnegie Mellon University},
month = {July},
year = {2008},
address = {Pittsburgh, PA},
}
2017-09-13T10:41:34+00:00