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    Cellular neural network based deformation simulation with haptic force feedback

    Access Status
    Fulltext not available
    Authors
    Zhong, Yongmin
    Shirinzadeh, B.
    Alici, G.
    Smith, J.
    Date
    2006
    Type
    Conference Paper
    
    Metadata
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    Citation
    Zhong, Y. and Shirinzadeh, B. and Alici, G. and Smith, J. 2006. Cellular neural network based deformation simulation with haptic force feedback, in The 9th International Workshop on Advanced Motion Control, Mar 27-29 2006, pp. 380-385. Istanbul, Turkey: IEEE.
    Source Title
    The 9th International Workshop on Advanced Motion Control
    Source Conference
    The 9th International Workshop on Advanced Motion Control
    DOI
    10.1109/AMC.2006.1631688
    URI
    http://hdl.handle.net/20.500.11937/10042
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a new methodology fordeformable object modelling by drawing an analogybetween cellular neural network (CNN) and elasticdeformation. The potential energy stored in an elasticbody as a result of a deformation caused by anexternal force is propagated among mass points by thenon-linear CNN activity. An improved CNN model isdeveloped for propagating the energy generated bythe external force on the object surface in the naturalmanner of Poisson equation. The proposedmethodology models non-linear materials with nonlinearCNN rather than geometric non-linearity in themost existing deformation methods. It can not onlydeal with large-range deformations, but it can alsoaccommodate isotropic, anisotropic andinhomogeneous materials by simply modifyingconstitutive constants.

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