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    Linear Time Stable PD Controllers for Physics-based Character Animation

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    Date
    2020
    Author
    Yin, Zhiqi ORCID
    Yin, KangKang
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    Abstract
    In physics-based character animation, Proportional-Derivative (PD) controllers are commonly used for tracking reference motions in motor control tasks. Stable PD (SPD) controllers significantly improve the numerical stability of traditional PD controllers and support large gains and large integration time steps during simulation [TLT11]. For an articulated rigid body system with n degrees of freedom, all SPD implementations to date, however, use an O(n3) dense matrix factorization based method. In this paper, we propose a linear time algorithm for SPD computation, which is based on Featherstone's forward dynamics formulation for articulated rigid body systems in generalized coordinates [Fea14]. We demonstrate the performance advantage of our algorithm by comparing with both the conventional dense matrix factorization based method and an alternative sparse matrix factorization based method.We show that the proposed algorithm provides superior stability when controlling complex models at large time steps. We further demonstrate that our algorithm can improve the learning speed and quality of a Deep Reinforcement Learning (DRL) system for physics-based character animation.
    BibTeX
    @article {10.1111:cgf.14113,
    journal = {Computer Graphics Forum},
    title = {{Linear Time Stable PD Controllers for Physics-based Character Animation}},
    author = {Yin, Zhiqi and Yin, KangKang},
    year = {2020},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.14113}
    }
    URI
    https://doi.org/10.1111/cgf.14113
    https://diglib.eg.org:443/handle/10.1111/cgf14113
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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