• DocumentCode
    2615778
  • Title

    Fast adaptation for effect-aware pushing

  • Author

    Ruiz-Ugalde, Federico ; Cheng, Gordon ; Beetz, Michael

  • Author_Institution
    Intell. Autonomous Syst. & Inst. for Cognitive Syst., Tech. Univ. Munchen, Munchen, Germany
  • fYear
    2011
  • fDate
    26-28 Oct. 2011
  • Firstpage
    614
  • Lastpage
    621
  • Abstract
    In order to produce robots that are more capable of skilled manipulation tasks, they must learn meaningful knowledge of how objects behave to external stimulus. With this knowledge a robot can predict the outcome of an action, control the object to serve a particular purpose, and together with reasoning, create or modify robot plans. In this paper we 1) build a mathematical compact model for planar sliding motion of an object, 2) show how a robot acquires the parameters of such a model; then how this is used to 3) predict pushing actions; and 4) to move an object from any1 position and orientation to another.
  • Keywords
    learning (artificial intelligence); robots; effect aware pushing; external stimulus; fast adaptation; mathematical compact model; planar sliding motion; pushing actions; robot knowledge; skilled manipulation; Cognition; Force; Friction; Mathematical model; Predictive models; Robot kinematics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Humanoid Robots (Humanoids), 2011 11th IEEE-RAS International Conference on
  • Conference_Location
    Bled
  • ISSN
    2164-0572
  • Print_ISBN
    978-1-61284-866-2
  • Electronic_ISBN
    2164-0572
  • Type

    conf

  • DOI
    10.1109/Humanoids.2011.6100863
  • Filename
    6100863