• DocumentCode
    3027518
  • Title

    Hierarchical, knowledge-oriented opto-acoustic scene analysis for humanoid robots and man-machine interaction

  • Author

    Machmer, T. ; Swerdlow, A. ; Kühn, B. ; Kroschel, K.

  • Author_Institution
    Inst. for Anthropomatics (IFA), Karlsruhe Inst. of Technol. (KIT), Karlsruhe, Germany
  • fYear
    2010
  • fDate
    3-7 May 2010
  • Firstpage
    2389
  • Lastpage
    2396
  • Abstract
    The opto-acoustic scene analysis is an extremely important as well as a challenging task for a humanoid robot. By the opto-acoustic scene analysis, the guided and autonomous exploration of the environment by means of acoustic and/or visual perception is meant. On the one hand, the perception ability is necessary to interact with humans in a humanoid way. On the other hand, the proximity of the robot has to be analyzed continuously, in order to enable the robot to fulfill its everyday tasks. Thereby, the greatest challenge lies in the wide variety of different perception tasks, e.g. detection, tracking, and identification of persons and different types of objects. This leads to the need of adapted, both, task- and context-dependent perception modules with specific requirements and abilities.
  • Keywords
    human-robot interaction; humanoid robots; mobile robots; autonomous exploration; context-dependent perception; guided exploration; hierarchical knowledge-oriented opto-acoustic scene analysis; humanoid robots; man-machine interaction; perception tasks; task-dependent perception; Human robot interaction; Humanoid robots; Identification of persons; Image analysis; Man machine systems; Object detection; Object oriented modeling; Real time systems; Robotics and automation; USA Councils; Opto-acoustic scene analysis; knowledgeoriented exploration of known and unknown objects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2010 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1050-4729
  • Print_ISBN
    978-1-4244-5038-1
  • Electronic_ISBN
    1050-4729
  • Type

    conf

  • DOI
    10.1109/ROBOT.2010.5509889
  • Filename
    5509889