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An Experimental Validation of the Polynomial Curvature Model: Identification and Optimal Control of a Soft Underwater Tentacle

Stella, Francesco and Obayashi, Nana and Della Santina, Cosimo and Hughes, Josie (2022) An Experimental Validation of the Polynomial Curvature Model: Identification and Optimal Control of a Soft Underwater Tentacle. IEEE Robotics and Automation Letters, 7 (4), pp. 11410-11417. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LRA.2022.3192887. ISSN 2377-3766.

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Official URL: https://ieeexplore.ieee.org/document/9835007

Abstract

The control possibilities for soft robots have long been hindered by the lack of accurate yet computationally treatable dynamic models of soft structures. Polynomial curvature models propose a solution to this quest for continuum slender structures. Nevertheless, the results produced with this class of models have been so far essentially theoretical. With the present work, we aim to provide a much-needed experimental validation to these recent theories. To this end, we focus on soft tentacles immersed in water. First, we propose an extension of the affine curvature model to underwater structures, considering the drag forces arising from the fluid-solid interaction. Then, we extensively test the model's capability to describe the system behavior across several shapes and working conditions. Finally, we validate model-based control policies, proposing and solving an optimal control problem for directional underwater swimming. Using the model we show an average increase of more than 3.5 times the swimming speed of a sinusoidal baseline controller, with some tentacles showing an improvement in excess of 5.5 times the baseline.

Item URL in elib:https://elib.dlr.de/192575/
Document Type:Article
Title:An Experimental Validation of the Polynomial Curvature Model: Identification and Optimal Control of a Soft Underwater Tentacle
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Stella, FrancescoCREATE Lab, EPFLUNSPECIFIEDUNSPECIFIED
Obayashi, NanaCREATE Lab, EPFLUNSPECIFIEDUNSPECIFIED
Della Santina, CosimoUNSPECIFIEDhttps://orcid.org/0000-0003-1067-1134UNSPECIFIED
Hughes, JosieCREATE Lab, EPFLUNSPECIFIEDUNSPECIFIED
Date:21 July 2022
Journal or Publication Title:IEEE Robotics and Automation Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:7
DOI:10.1109/LRA.2022.3192887
Page Range:pp. 11410-11417
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:2377-3766
Status:Published
Keywords:Modeling, control, and learning for soft robots, system identification, flexible robotics
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Robot Dynamics & Simulation [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Strobl, Dr. Klaus H.
Deposited On:19 Dec 2022 07:25
Last Modified:19 Sep 2023 11:46

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