QUT ePrints

Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle

Corke, Peter, Hrabar, S., Peterson, R., Rus, D., Saripalli, S., & Sukhatme, G. (2004) Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle. In Proceedings - IEEE International Conference on Robotics and Automation.

[img] Published Version (PDF 687kB)

    Abstract

    We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.).

    Citations:

    49 times in Scopus
    Search Google Scholar™
    16 times in Web of Science

    Citation countsare sourced monthly from Scopus and Web of Science citation databases.

    These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.

    Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

    Full-text downloads:

    94 since deposited on 17 Jun 2010
    67 in the past twelve months

    Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

    More statistics...
    ID Code: 32777
    Item Type: Conference Paper
    Keywords: data mules, sensor networks
    Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
    Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
    Past > Schools > School of Engineering Systems
    Deposited On: 17 Jun 2010 16:35
    Last Modified: 16 Sep 2010 22:27

    Export: EndNote | Dublin Core | BibTeX

    Repository Staff Only: item control page