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dc.contributor.authorConnolly, Fionnuala
dc.contributor.authorWalsh, Conor
dc.contributor.authorBertoldi, Katia
dc.date.accessioned2019-10-03T14:38:21Z
dc.date.issued2017
dc.identifier.citationConnolly, Fionnuala, Conor J. Walsh, and Katia Bertoldi. 2016. “Automatic Design of Fiber-Reinforced Soft Actuators for Trajectory Matching.” Proceedings of the National Academy of Sciences 114 (1): 51–56. https://doi.org/10.1073/pnas.1615140114.
dc.identifier.issn0027-8424
dc.identifier.issn0744-2831
dc.identifier.issn1091-6490
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:41461193*
dc.description.abstractSoft actuators are the components responsible for producing motion in soft robots. Although soft actuators have allowed for a variety of innovative applications, there is a need for design tools that can help to efficiently and systematically design actuators for particular functions. Mathematical modeling of soft actuators is an area that is still in its infancy but has the potential to provide quantitative insights into the response of the actuators. These insights can be used to guide actuator design, thus accelerating the design process. Here, we study fluid-powered fiber-reinforced actuators, because these have previously been shown to be capable of producing a wide range of motions. We present a design strategy that takes a kinematic trajectory as its input and uses analytical modeling based on nonlinear elasticity and optimization to identify the optimal design parameters for an actuator that will follow this trajectory upon pressurization. We experimentally verify our modeling approach, and finally we demonstrate how the strategy works, by designing actuators that replicate the motion of the index finger and thumb.
dc.language.isoen_US
dc.publisherNational Academy of Sciences
dash.licenseLAA
dc.titleAutomatic design of fiber-reinforced soft actuators for trajectory matching
dc.typeJournal Article
dc.description.versionVersion of Record
dc.relation.journalProceedings of the National Academy of Sciences of the United States of America
dash.depositing.authorBertoldi, Katia::51c5997f58e8affc1eaad61d594ecb09::600
dc.date.available2019-10-03T14:38:21Z
dash.workflow.comments1Science Serial ID 91434
dc.identifier.doi10.1073/pnas.1615140114
dash.source.volume114;1
dash.source.page51


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