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    Accelerating Hybrid Systems Differential Dynamic Programming

    Source: ASME Letters in Dynamic Systems and Control:;2023:;volume( 003 ):;issue: 001::page 11002-1
    Author:
    Nganga, John N.
    ,
    Wensing, Patrick M.
    DOI: 10.1115/1.4056747
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This letter presents approaches that reduce the computational demand of including second-order dynamics sensitivity information into optimization algorithms for robots in contact with the environment. A full second-order differential dynamic programming (DDP) algorithm is presented where all the necessary dynamics partial derivatives are computed with the same complexity as DDP’s first-order counterpart, the iterative linear quadratic regulator (iLQR). Compared to linearized models used in iLQR, DDP more accurately represents the dynamics locally, but it is not often used since the second-order partials of the dynamics are tensorial and expensive to compute. This work illustrates how to avoid the need for computing the derivative tensor by instead leveraging reverse-mode accumulation of derivatives, extending previous work for unconstrained systems. We exploit the structure of the contact-constrained dynamics in this process. The performance of the proposed approaches is benchmarked with a simulated model of the MIT Mini Cheetah executing a bounding gait.
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      Accelerating Hybrid Systems Differential Dynamic Programming

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4291833
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    contributor authorNganga, John N.
    contributor authorWensing, Patrick M.
    date accessioned2023-08-16T18:19:48Z
    date available2023-08-16T18:19:48Z
    date copyright2/28/2023 12:00:00 AM
    date issued2023
    identifier issn2689-6117
    identifier otheraldsc_3_1_011002.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4291833
    description abstractThis letter presents approaches that reduce the computational demand of including second-order dynamics sensitivity information into optimization algorithms for robots in contact with the environment. A full second-order differential dynamic programming (DDP) algorithm is presented where all the necessary dynamics partial derivatives are computed with the same complexity as DDP’s first-order counterpart, the iterative linear quadratic regulator (iLQR). Compared to linearized models used in iLQR, DDP more accurately represents the dynamics locally, but it is not often used since the second-order partials of the dynamics are tensorial and expensive to compute. This work illustrates how to avoid the need for computing the derivative tensor by instead leveraging reverse-mode accumulation of derivatives, extending previous work for unconstrained systems. We exploit the structure of the contact-constrained dynamics in this process. The performance of the proposed approaches is benchmarked with a simulated model of the MIT Mini Cheetah executing a bounding gait.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleAccelerating Hybrid Systems Differential Dynamic Programming
    typeJournal Paper
    journal volume3
    journal issue1
    journal titleASME Letters in Dynamic Systems and Control
    identifier doi10.1115/1.4056747
    journal fristpage11002-1
    journal lastpage11002-8
    page8
    treeASME Letters in Dynamic Systems and Control:;2023:;volume( 003 ):;issue: 001
    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
    yabeshDSpacePersian