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.
PDF
- Postprint version (accepted manuscript)
598kB |
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: |
| ||||||||||||||||||||
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 |
Repository Staff Only: item control page