Local Models for Data Driven Inverse Kinematics of Soft Robots
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2018Pay-Per-View via TIB Hannover:
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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}
}
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}
}