This paper presents an efficient numerical formulation for the prediction of realistic postures. This problem is defined by the method (or procedure) used to predict the posture of a human, given a point in the reachable space. The exposition addresses (1) the determination whether a point is reachable (i.e., does is it exist within the reach envelope) and (2) the calculation of a posture for a given point. While many researchers have used either statistical models of empirical data or the traditional geometric inverse kinematics method for posture prediction, we present a method based on kinematics for modeling, but one that uses optimization of a cost function to predict a realistic posture. It is shown that this method replicates the human mind in selecting a posture from an infinite number of possible postures. We illustrate the methodology and an accompanying experimental code through a planar and a spatial example, and validation using commercial human modeling and simulation code.


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    Titel :

    Realistic Posture Prediction for Maximum Dexterity


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Duncan, Jerry (Autor:in) / Abdel-Malek, Karim (Autor:in) / Jaber, Mohamad (Autor:in) / Yu, Wei (Autor:in)

    Kongress:

    Digital Human Modeling For Design And Engineering Conference And Exhibition ; 2001



    Erscheinungsdatum :

    26.06.2001




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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