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    Local Models for Data Driven Inverse Kinematics of Soft Robots

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    Date
    2018
    Author
    Holsten, Fredrik
    Darkner, Sune
    Engell-Nørregård, Morten P.
    Erleben, Kenny
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    Abstract
    Soft robots are attractive because they have the potential of being safer, faster and cheaper than traditional rigid robots. If we can predict the shape of a soft robot for a given set of control parameters, then we can solve the inverse problem: to find an optimal set of control parameters for a given shape. This work takes a data-driven approach to create multiple local inverse models. This has two benefits: (1) We overcome the reality gap and (2) we gain performance and naive parallelism from using local models. Furthermore, we empirically prove that our approach outperforms a higher order global model.
    BibTeX
    @inproceedings {a.20181186,
    booktitle = {Eurographics/ ACM SIGGRAPH Symposium on Computer Animation - Posters},
    editor = {Skouras, Melina},
    title = {{Local Models for Data Driven Inverse Kinematics of Soft Robots}},
    author = {Holsten, Fredrik and Darkner, Sune and Engell-Nørregård, Morten P. and Erleben, Kenny},
    year = {2018},
    publisher = {The Eurographics Association},
    ISSN = {1727-5288},
    ISBN = {978-3-03868-070-3},
    DOI = {10.2312/sca.20181186}
    }
    URI
    https://doi.org/10.2312/sca.20181186
    https://diglib.eg.org:443/handle/10.2312/sca20181186
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