• DocumentCode
    2021438
  • Title

    Multi-view operator control unit to improve situation awareness in USAR missions

  • Author

    Larochelle, Benoit ; Kruijff, Geert-Jan M.

  • Author_Institution
    German Res. Center for Artificial Intell. (DFKI GmbH), Saarbrücken, Germany
  • fYear
    2012
  • fDate
    9-13 Sept. 2012
  • Firstpage
    1103
  • Lastpage
    1108
  • Abstract
    In urban search and rescue (USAR) missions, manually controlling robots is difficult, in large part due to low situation awareness (SA) provided by operator control units (OCUs). This paper looks at state-of-the-art OCUs to identify seven fundamental problems to be resolved. Next, the design and implementation of a multi-view multi-modal OCU are presented. This OCU follows a large set of design guidlines and also features novel techniques for a human operator to remotely interact with a man-portable ground robot. The system was evaluated in a high fidelity tunnel accident simulation at a fire fighting training center. The OCU allowed training and collisions to remain low, while SA was improved. Qualitative observations are also discussed, such that end-users do not often choose the optimal views in the OCU for the tasks at hand.
  • Keywords
    accidents; emergency services; human-robot interaction; mobile robots; USAR missions; fighting training center; high fidelity tunnel accident simulation; man-portable ground robot; multiview multimodal OCU; multiview operator control unit; situation awareness; urban search and rescue; Cameras; Collision avoidance; Feeds; Robot vision systems; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    RO-MAN, 2012 IEEE
  • Conference_Location
    Paris
  • ISSN
    1944-9445
  • Print_ISBN
    978-1-4673-4604-7
  • Electronic_ISBN
    1944-9445
  • Type

    conf

  • DOI
    10.1109/ROMAN.2012.6343896
  • Filename
    6343896