• Login
    View Item 
    •   Eurographics DL Home
    • Computer Graphics Forum
    • Volume 35 (2016)
    • 35-Issue 2
    • View Item
    •   Eurographics DL Home
    • Computer Graphics Forum
    • Volume 35 (2016)
    • 35-Issue 2
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Data-guided Model Predictive Control Based on Smoothed Contact Dynamics

    Thumbnail
    View/Open
    v35i2pp533-543.pdf (868.0Kb)
    fbmpc_suppl_a.pdf (282.8Kb)
    fbmpc_suppl_b.pdf (78.13Kb)
    fbmpc_video.avi (22.62Mb)
    Date
    2016
    Author
    Han, Daseong
    Eom, Haegwang
    Noh, Junyong ORCID
    Shin, Joseph S. (formerly Sung Yong)
    Pay-Per-View via TIB Hannover:

    Try if this item/paper is available.

    Metadata
    Show full item record
    Abstract
    In this paper, we propose an efficient data-guided method based on Model Predictive Control (MPC) to synthesize a full-body motion. Guided by a reference motion, our method repeatedly plans the full-body motion to produce an optimal control policy for predictive control while sliding the fixed-span window along the time axis. Based on this policy, the method computes the joint torques of a character at every time step. Together with contact forces and external perturbations if there are any, the joint torques are used to update the state of the character. Without including the contact forces in the control vector, our formulation of the trajectory optimization problem enables automatic adjustment of contact timings and positions for balancing in response to environmental changes and external perturbations. For efficiency, we adopt derivative-based trajectory optimization on top of state-of-the-art smoothed contact dynamics. Use of derivatives enables our method to run much faster than the existing sampling-based methods. In order to further accelerate the performance of MPC, we propose efficient numerical differentiation of the system dynamics of a full-body character based on two schemes: data reuse and data interpolation. The former scheme exploits data dependency to reuse physical quantities of the system dynamics at near-by time points. The latter scheme allows the use of derivatives at sparse sample points to interpolate those at other time points in the window. We further accelerate evaluation of the system dynamics by exploiting the sparsity of physical quantities such as Jacobian matrix resulting from the tree-like structure of the articulated body. Through experiments, we show that the proposed method efficiently can synthesize realistic motions such as locomotion, dancing, gymnastic motions, and martial arts at interactive rates using moderate computing resources.
    BibTeX
    @article {10.1111:cgf.12853,
    journal = {Computer Graphics Forum},
    title = {{Data-guided Model Predictive Control Based on Smoothed Contact Dynamics}},
    author = {Han, Daseong and Eom, Haegwang and Noh, Junyong and Shin, Joseph S. (formerly Sung Yong)},
    year = {2016},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.12853}
    }
    URI
    http://dx.doi.org/10.1111/cgf.12853
    Collections
    • 35-Issue 2
    • EG 2016 - Full Papers - CGF 35-Issue 2

    Eurographics Association copyright © 2013 - 2022 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA
     

     

    Browse

    All of Eurographics DLCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    BibTeX | TOC

    Create BibTeX Create Table of Contents

    Eurographics Association copyright © 2013 - 2022 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA