• DocumentCode
    2078048
  • Title

    Fault-diagnosis of subsea robots using neuro-symbolic hybrid systems

  • Author

    Deuker, B. ; Perrier, M. ; Amy, B.

  • Author_Institution
    IFREMER, Subsea Robotics & Artificial Intelligence Lab., La Seyne-sur-Mer, France
  • Volume
    2
  • fYear
    1998
  • fDate
    28 Sep-1 Oct 1998
  • Firstpage
    830
  • Abstract
    We describe a diagnosis phase, part of a study currently performed on subsea robots health monitoring. The overall objective of this study is to allow a subsea robot with sub-system failure to keep executing its mission with a certain level of performance. The current development of the diagnosis phase is based on the use of neuro-symbolic hybrid systems. With this solution, the system is able to learn when it meets unforeseen failures
  • Keywords
    computerised monitoring; fault diagnosis; fault tolerance; mobile robots; neurocontrollers; underwater vehicles; fault tolerance; fault-diagnosis; health monitoring; hybrid neural symbolic systems; model based diagnosis; subsea robots; underwater vehicles; Actuators; Artificial intelligence; Condition monitoring; Failure analysis; Intelligent robots; Laboratories; Phase detection; Robot sensing systems; Testing; Underwater vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    OCEANS '98 Conference Proceedings
  • Conference_Location
    Nice
  • Print_ISBN
    0-7803-5045-6
  • Type

    conf

  • DOI
    10.1109/OCEANS.1998.724354
  • Filename
    724354