IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v44y2013i5p831-852.html
   My bibliography  Save this article

Autonomous mission management for UAVs using soar intelligent agents

Author

Listed:
  • Paolo Gunetti
  • Haydn Thompson
  • Tony Dodd

Abstract

State-of-the-art unmanned aerial vehicles (UAVs) are typically able to autonomously execute a pre-planned mission. However, UAVs usually fly in a very dynamic environment which requires dynamic changes to the flight plan; this mission management activity is usually tasked to human supervision. Within this article, a software system that autonomously accomplishes the mission management task for a UAV will be proposed. The system is based on a set of theoretical concepts which allow the description of a flight plan and implemented using a combination of Soar intelligent agents and traditional control techniques. The system is capable of automatically generating and then executing an entire flight plan after being assigned a set of objectives. This article thoroughly describes all system components and then presents the results of tests that were executed using a realistic simulation environment.

Suggested Citation

  • Paolo Gunetti & Haydn Thompson & Tony Dodd, 2013. "Autonomous mission management for UAVs using soar intelligent agents," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(5), pages 831-852.
    • Handle: RePEc:taf:tsysxx:v:44:y:2013:i:5:p:831-852
    DOI: 10.1080/00207721.2011.626902
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2011.626902
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2011.626902?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hyondong Oh & Seungkeun Kim & Hyo-Sang Shin & Antonios Tsourdos & Brian A. White, 2014. "Behaviour recognition of ground vehicle using airborne monitoring of unmanned aerial vehicles," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 2499-2514, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tsysxx:v:44:y:2013:i:5:p:831-852. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.