Learning 3D shape proprioception for continuum soft robots with multiple magnetic sensors
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00364428" target="_blank" >RIV/68407700:21730/22:00364428 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1039/d2sm00914e" target="_blank" >https://doi.org/10.1039/d2sm00914e</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1039/d2sm00914e" target="_blank" >10.1039/d2sm00914e</a>
Alternative languages
Result language
angličtina
Original language name
Learning 3D shape proprioception for continuum soft robots with multiple magnetic sensors
Original language description
Sensing the shape of continuum soft robots without obstructing their movements and modifying their natural softness requires innovative solutions. This letter proposes to use magnetic sensors fully integrated into the robot to achieve proprioception. Magnetic sensors are compact, sensitive, and easy to integrate into a soft robot. We also propose a neural architecture to make sense of the highly nonlinear relationship between the perceived intensity of the magnetic field and the shape of the robot. By injecting a priori knowledge from the kinematic model, we obtain an effective yet data-efficient learning strategy. We first demonstrate in simulation the value of this kinematic prior by investigating the proprioception behavior when varying the sensor configuration, which does not require us to re-train the neural network. We validate our approach in experiments involving one soft segment containing a cylindrical magnet and three magnetoresistive sensors. During the experiments, we achieve mean relative errors of 4.5%.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Soft Matter
ISSN
1744-683X
e-ISSN
1744-6848
Volume of the periodical
19
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
13
Pages from-to
44-56
UT code for WoS article
000894145800001
EID of the result in the Scopus database
2-s2.0-85144234485