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    Vectorized Formulation of Newton-Euler Dynamics for Efficiently Computing Three-Dimensional Folding Chains

    Source: Journal of Mechanisms and Robotics:;2022:;volume( 014 ):;issue: 006::page 61007-1
    Author:
    Fass
    ,
    T. H.;Hao
    ,
    Guangbo;Cantillon-Murphy
    ,
    Pádraig
    DOI: 10.1115/1.4054311
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Within the wide field of self-assembly, the self-folding chain has unique potential for reliable and repeatable assembly of three-dimensional structures as demonstrated by protein biosynthesis. This potential could be translated to self-reconfiguring robots by utilizing magnetic forces between the chain components as a driving force for the folding process. Due to the constraints introduced by the joints between the chain components, simulation of the dynamics of longer chains is computationally intensive and challenging. This article presents a novel analytical approach to formulate the Newton–Euler dynamics of a self-reconfiguring chain in a single vectorized differential equation. The vectorized differential equation allows for a convenient implementation of a parallel processing architecture using single instruction multiple data (SIMD) or graphical processing unit (GPU) computation and as a result can improve simulation time of rigid body chains. Properties of existing interpretations of the Newton–Euler and Euler–Lagrange algorithms are discussed in their efficiency to compute the dynamics of rigid body chains. Finally, GPU and SIMD-supported simulation, based on the vectorized Newton–Euler equations described in this article, are compared, showing a significant improvement in computation time using GPU architecture for long chains with certain chain geometry.
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      Vectorized Formulation of Newton-Euler Dynamics for Efficiently Computing Three-Dimensional Folding Chains

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4287547
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    contributor authorFass
    contributor authorT. H.;Hao
    contributor authorGuangbo;Cantillon-Murphy
    contributor authorPádraig
    date accessioned2022-08-18T13:10:08Z
    date available2022-08-18T13:10:08Z
    date copyright6/6/2022 12:00:00 AM
    date issued2022
    identifier issn1942-4302
    identifier otherjmr_14_6_061007.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4287547
    description abstractWithin the wide field of self-assembly, the self-folding chain has unique potential for reliable and repeatable assembly of three-dimensional structures as demonstrated by protein biosynthesis. This potential could be translated to self-reconfiguring robots by utilizing magnetic forces between the chain components as a driving force for the folding process. Due to the constraints introduced by the joints between the chain components, simulation of the dynamics of longer chains is computationally intensive and challenging. This article presents a novel analytical approach to formulate the Newton–Euler dynamics of a self-reconfiguring chain in a single vectorized differential equation. The vectorized differential equation allows for a convenient implementation of a parallel processing architecture using single instruction multiple data (SIMD) or graphical processing unit (GPU) computation and as a result can improve simulation time of rigid body chains. Properties of existing interpretations of the Newton–Euler and Euler–Lagrange algorithms are discussed in their efficiency to compute the dynamics of rigid body chains. Finally, GPU and SIMD-supported simulation, based on the vectorized Newton–Euler equations described in this article, are compared, showing a significant improvement in computation time using GPU architecture for long chains with certain chain geometry.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleVectorized Formulation of Newton-Euler Dynamics for Efficiently Computing Three-Dimensional Folding Chains
    typeJournal Paper
    journal volume14
    journal issue6
    journal titleJournal of Mechanisms and Robotics
    identifier doi10.1115/1.4054311
    journal fristpage61007-1
    journal lastpage61007-6
    page6
    treeJournal of Mechanisms and Robotics:;2022:;volume( 014 ):;issue: 006
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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