TU Berlin

Main document

Literature Database Entry


Juergen Eckert, Falko Dressler and Reinhard German, "Sensor Network Support for Real-time Indoor Localization of Four-rotor Flying Robots," Proceedings of 8. GI/ITG KuVS Fachgespräch Drahtlose Sensornetze (FGSN 2009), Hamburg, Germany, August 2009, pp. 1–4.


We present a sensor network based indoor localization system that uses ultrasonic distance measurements for real-time localization of flying four-rotor robots. Such quadrocopters are on-board sensor controlled systems. They are very sensitive to lateral drifts, which cannot be compensated by mounted sensors. In our work, we provide a framework for time-of-flight based localization systems relying on ultrasonic sensors. It is optimized for use in sensor nodes with low computational power and limited memory. Nevertheless, it offers scalability and high accuracy even with erroneous measurements. We implemented the system in our lab using ultrasound sensor that are light enough to be carried around by the flying object. Using this real-time localization system, a position controller can be implemented to maintain a given position or course.

Quick access

Authors' Version PDF (PDF on this web site)
BibTeX BibTeX


Juergen Eckert
Falko Dressler
Reinhard German

BibTeX reference

    author = {Eckert, Juergen and Dressler, Falko and German, Reinhard},
    title = {{Sensor Network Support for Real-time Indoor Localization of Four-rotor Flying Robots}},
    pages = {1--4},
    address = {Hamburg, Germany},
    booktitle = {8. GI/ITG KuVS Fachgespr{\"{a}}ch Drahtlose Sensornetze (FGSN 2009)},
    month = {8},
    year = {2009},

Copyright notice

Links to final or draft versions of papers are presented here 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. In most cases, these works may not be reposted or distributed for commercial purposes without the explicit permission of the copyright holder.

The following applies to all papers listed above that have IEEE copyrights: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

The following applies to all papers listed above that are in submission to IEEE conference/workshop proceedings or journals: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

The following applies to all papers listed above that have ACM copyrights: ACM COPYRIGHT NOTICE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or permissions@acm.org.

The following applies to all SpringerLink papers listed above that have Springer Science+Business Media copyrights: The original publication is available at www.springerlink.com.

This page was automatically generated using BibDB and bib2web.


Featured Paper