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dc.contributor.author
van Diepen, Merel
dc.contributor.author
Shea, Kristina
dc.date.accessioned
2022-07-19T07:46:17Z
dc.date.available
2022-05-10T07:12:41Z
dc.date.available
2022-05-10T11:53:53Z
dc.date.available
2022-06-14T07:30:24Z
dc.date.available
2022-07-19T07:46:17Z
dc.date.issued
2022-08
dc.identifier.issn
1050-0472
dc.identifier.issn
1528-9001
dc.identifier.other
10.1115/1.4054522
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/546183
dc.description.abstract
Recently, the field of soft robotics has received considerable attention due to their potential to increase the safety of human-robot interaction. The design of soft robots poses great challenges, for example, the co-design of morphology and actuation, making designing them by hand a trial-and-error process. Earlier work by the authors proposes a Computational Design Synthesis (CDS) method for the automated design of virtual, soft locomotion robot morphologies. This work extends the CDS method for morphologies with the automated co-design of actuation. Two methods are considered. In the first method, the actuation of designs is described by Parametric Actuation Curves (PACs) that model feedforward actuation patterns. For every morphology in the design process, a set of PACs are optimized that assume symmetric and cyclic gaits. The second method, Soft Actor-Critic (SAC) reinforcement learning, removes this assumption as well as modeling feedback control for comparison. Adding PAC optimization to the CDS method is shown to improve the performance of the resulting designs and to achieve better results within less design iterations. SAC is, however, deemed less effective, due to the need for design specific problem tuning for each new morphology. The SAC experiments also show that the best found soft robot gaits are symmetric and cyclic, although not constrained in the SAC problem formulation, thus verifying the assumptions made in the PAC formulation. To validate the search space modeled in the co-design CDS method, a state-of-the-art soft robot is replicated and compared.
en_US
dc.language.iso
en
en_US
dc.publisher
American Society of Mechanical Engineers
en_US
dc.subject
computer-aided design
en_US
dc.subject
conceptual design
en_US
dc.subject
design automation
en_US
dc.subject
generative design
en_US
dc.subject
shape grammars
en_US
dc.title
Co-Design of the Morphology and Actuation of Soft Robots for Locomotion
en_US
dc.type
Journal Article
dc.date.published
2022-06-13
ethz.journal.title
Journal of Mechanical Design
ethz.journal.volume
144
en_US
ethz.journal.issue
8
en_US
ethz.journal.abbreviated
J. Mech. Des.
ethz.pages.start
083305
en_US
ethz.size
13 p.
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02665 - Inst. f. Design, Mat. und Fabrikation / Inst. of Design, Materials a Fabrication::03954 - Shea, Kristina / Shea, Kristina
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02665 - Inst. f. Design, Mat. und Fabrikation / Inst. of Design, Materials a Fabrication::03954 - Shea, Kristina / Shea, Kristina
en_US
ethz.date.deposited
2022-05-10T07:12:47Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2022-06-14T07:30:49Z
ethz.rosetta.lastUpdated
2023-02-07T04:43:03Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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