Home/Range-only SLAM with Interpolated Range Data

Range-only SLAM with Interpolated Range Data

Athanasios Kehagias, Joseph Djugash and Sanjiv Singh
Tech. Report, CMU-RI-TR-06-26, Robotics Institute, Carnegie Mellon University, May, 2006

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 a series of recent papers Singh et al. have explored the idea of Simultaneous Localization and Mapping (SLAM) using range-only measurements. These measurements, obtained from radio or sonar sensors, come at irregular time intervals. In this report we explore the use of interpolation to generate data equally spaced in time, in order to improve the performance of SLAM algorithms. We test this idea on several (simulated and real) robot paths and two SLAM algorithms: an online Extended Kalman Filter (EKF) algorithm and an offline batch optimization algorithm.

BibTeX Reference
@techreport{Kehagias-2006-9461,
title = {Range-only SLAM with Interpolated Range Data},
author = {Athanasios Kehagias and Joseph Djugash and Sanjiv Singh},
keyword = {Localization, mapping, SLAM, optimization, Kalman filter},
school = {Robotics Institute , Carnegie Mellon University},
month = {May},
year = {2006},
number = {CMU-RI-TR-06-26},
address = {Pittsburgh, PA},
}
2017-09-13T10:42:47+00:00