Soft Robotics: Review of Fluid‐Driven Intrinsically Soft Devices; Manufacturing, Sensing, Control, and Applications in Human‐Robot Interaction
By Panagiotis Polygerinos, Nikolaus Correll, Stephen A. Morin, Bobak Mosadegh, Cagdas Denizel Onal, Kirstin H. Petersen, Matteo Cianchetti, Michael Thomas Tolley, Robert F. Shepherd. 2017
953 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Condensed Matter Physics
View Paper: https://www.semanticscholar.org/paper/d8cdebedb57d9bc3f0d3039cc20ca425a7cb216f
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In Biomedical Engineering
- Michael Thomas Tolley
- Cecilia Laschi
- Thomas George Thuruthel
- Daniela Rus
- Matteo Cianchetti
- Cosimo Della Santina
- Christian Duriez
- Barbara Mazzolai
In Condensed Matter Physics
Citations in the corpus
- Soft robot perception using embedded soft sensors and recurrent neural networks (2019, background): “However, the modeling of soft sensors is challenged by inconsistencies in their manufacture and nonlinearities in their dynamics (4, 5, 6).”
- Electronics-free pneumatic circuits for controlling soft-legged robots (2021, background): “, electronics, pumps, and valves) required for their actuation and control (7).”
- Real-time dynamics of soft and continuum robots based on Cosserat rod models (2019, background): “Modeling approaches vary; it can be adequate to assume direct input control of fluid pressure, but in some cases the fluid response is sufficiently slow that it is more appropriate to use sophisticated fluid dynamics models (Polygerinos et al., 2017).”