• DocumentCode
    2516563
  • Title

    Persistent autonomy artificial intelligence or biomimesis?

  • Author

    Lane, David M.

  • Author_Institution
    Ocean Syst. Lab., Heriot-Watt Univ. Edinburgh, Edinburgh, UK
  • fYear
    2012
  • fDate
    24-27 Sept. 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    We seek to develop autonomous robots that can operate and interact unsupervised for extended lengths of time in unknown environments, adapting their purpose in response to events and goals, learning from successes and failures, recovering from errors in execution whilst monitoring and maintaining self health. Such persistent autonomy is a challenging ambition, and the subject of an increasingly intense research effort. Two broad approaches have evolved, one rooted in artificial intelligence research from the 1970s onward, and the other in studies of animals and even plants that nature has evolved over millennia. Both offer opportunities and challenges in implementation. This paper presents a snapshot of recent and ongoing developments from each approach, and offers some perspectives on the potential that each offers.
  • Keywords
    autonomous underwater vehicles; biomimetics; health care; learning (artificial intelligence); mobile robots; telerobotics; unsupervised learning; artificial intelligence; autonomous robots; biomimesis; health maintenance; health monitoring; persistent autonomy; two broad approaches; unsupervised interaction; Computer architecture; Learning systems; Marine animals; Ontologies; Planning; Robot sensing systems; adaptive planning; architecture; artificial intelligence; autonomous underwater robot; bioinspired; biomimesis; biosonar; electric sense; fish swimming; flow sense; ontology; persistent autonomy; skill learning; soft robot; world model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Autonomous Underwater Vehicles (AUV), 2012 IEEE/OES
  • Conference_Location
    Southampton
  • ISSN
    1522-3167
  • Print_ISBN
    978-1-4577-2055-0
  • Electronic_ISBN
    1522-3167
  • Type

    conf

  • DOI
    10.1109/AUV.2012.6380719
  • Filename
    6380719