Optimum control strategies for maximum thrust production in underwater undulatory swimming Article Swipe
Li Fu
,
Sardor Israilov
,
Jesús Sánchez-Rodríguez
,
Christophe Brouzet
,
Guillaume Allibert
,
Christophe Raufaste
,
Médéric Argentina
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2309.14025
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2309.14025
Fishes, cetaceans, and many other aquatic vertebrates undulate their bodies to propel themselves through water. Swimming requires an intricate interplay between sensing the environment, making decisions, controlling internal dynamics, and moving the body in interaction with the external medium. Within this sequence of actions initiating locomotion, biological and physical laws manifest complex and nonlinear effects, which does not prevent natural swimmers to demonstrate efficient movement. This raises two complementary questions: how to model this intricacy and how to abstract it for practical swimming. In the context of robotics, the second question is of paramount importance to build efficient artificial swimmers driven by digital signals and mechanics. In this study, we tackle these two questions by leveraging a biomimetic robotic swimmer as a platform for investigating optimal control strategies for thrust generation. Through a combination of machine learning techniques and intuitive models, we identify a control signal that maximizes thrust production. Optimum tail-beat frequency and amplitude result from the subtle interplay between the swimmer's internal dynamics and its interaction with the surrounding fluid. We then propose a practical implementation for autonomous robotic swimmers that requires no prior knowledge of systems or equations. Direct fluid-structure simulations confirms the effectiveness and reliability of the proposed approach. Hence, our findings bridge fluid dynamics, robotics, and biology, providing valuable insights into the physics of aquatic locomotion
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2309.14025
- https://arxiv.org/pdf/2309.14025
- OA Status
- green
- References
- 6
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387076220
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387076220Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2309.14025Digital Object Identifier
- Title
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Optimum control strategies for maximum thrust production in underwater undulatory swimmingWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
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2023-09-25Full publication date if available
- Authors
-
Li Fu, Sardor Israilov, Jesús Sánchez-Rodríguez, Christophe Brouzet, Guillaume Allibert, Christophe Raufaste, Médéric ArgentinaList of authors in order
- Landing page
-
https://arxiv.org/abs/2309.14025Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2309.14025Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2309.14025Direct OA link when available
- Concepts
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Thrust, Robotics, Artificial intelligence, Computer science, Context (archaeology), Underwater, Biomimetics, Robot, Control engineering, Engineering, Aerospace engineering, Biology, Geology, Oceanography, PaleontologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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6Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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