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    • 39-Issue 8
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    ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills

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    Date
    2020
    Author
    Xie, Zhaoming
    Ling, Hung Yu
    Kim, Nam Hee ORCID
    Panne, Michiel van de
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    Abstract
    Humans are highly adept at walking in environments with foot placement constraints, including stepping-stone scenarios where footstep locations are fully constrained. Finding good solutions to stepping-stone locomotion is a longstanding and fundamental challenge for animation and robotics. We present fully learned solutions to this difficult problem using reinforcement learning. We demonstrate the importance of a curriculum for efficient learning and evaluate four possible curriculum choices compared to a non-curriculum baseline. Results are presented for a simulated humanoid, a realistic bipedal robot simulation and a monster character, in each case producing robust, plausible motions for challenging stepping stone sequences and terrains.
    BibTeX
    @article {10.1111:cgf.14115,
    journal = {Computer Graphics Forum},
    title = {{ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills}},
    author = {Xie, Zhaoming and Ling, Hung Yu and Kim, Nam Hee and Panne, Michiel van de},
    year = {2020},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.14115}
    }
    URI
    https://doi.org/10.1111/cgf.14115
    https://diglib.eg.org:443/handle/10.1111/cgf14115
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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