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    Simulation of Human Motion Data using Short-Horizon Model-Predictive Control

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    Date
    2008
    Author
    Da Silva, M.
    Abe, Y.
    Popovic, J.
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    Abstract
    Many data-driven animation techniques are capable of producing high quality motions of human characters. Few techniques, however, are capable of generating motions that are consistent with physically simulated environments. Physically simulated characters, in contrast, are automatically consistent with the environment, but their motions are often unnatural because they are difficult to control. We present a model-predictive controller that yields natural motions by guiding simulated humans toward real motion data. During simulation, the predictive component of the controller solves a quadratic program to compute the forces for a short window of time into the future. These forces are then applied by a low-gain proportional-derivative component, which makes minor adjustments until the next planning cycle. The controller is fast enough for interactive systems such as games and training simulations. It requires no precomputation and little manual tuning. The controller is resilient to mismatches between the character dynamics and the input motion, which allows it to track motion capture data even where the real dynamics are not known precisely. The same principled formulation can generate natural walks, runs, and jumps in a number of different physically simulated surroundings.
    BibTeX
    @article {10.1111:j.1467-8659.2008.01134.x,
    journal = {Computer Graphics Forum},
    title = {{Simulation of Human Motion Data using Short-Horizon Model-Predictive Control}},
    author = {Da Silva, M. and Abe, Y. and Popovic, J.},
    year = {2008},
    publisher = {The Eurographics Association and Blackwell Publishing Ltd},
    ISSN = {1467-8659},
    DOI = {10.1111/j.1467-8659.2008.01134.x}
    }
    URI
    http://dx.doi.org/10.1111/j.1467-8659.2008.01134.x
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    • 27-Issue 2
    • Full Papers 2008 - CGF 27-Issue 2

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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.
    TUGFhA