Automatic segmentation of fish midlines for optimizing robot design

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Automatic segmentation of fish midlines for optimizing robot design. / Fetherstonhaugh, Samuel E.A.W.; Shen, Qiang; Akanyeti, Otar.

In: Bioinspiration and Biomimetics, Vol. 16, No. 4, 046005, 20.05.2021.

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@article{c223dc0c32834a9f863e9f1be2cd02e7,
title = "Automatic segmentation of fish midlines for optimizing robot design",
abstract = "While fish use continuous and flexible bodies to propel themselves, fish robots are often made from interconnected segments. How many segments do robots need to represent fish movements accurately? We propose a new method to automatically determine parsimonious robot models from actual fish data. We first identify key bending points (i.e., joint positions) along the body and then study the concerted movement of the segments so that the difference between actual fish and modelled bending kinematics is minimized. To demonstrate the utility of our method, we analyse the steady swimming kinematics of 10 morphologically distinct fish species. Broadly classified as sub-carangiform (e.g., rainbow trout) and carangiform (e.g., crevalle jack) swimmers, these species exhibit variations in the way they undulate when traditional parameters (including head and tail beat amplitudes, body wavelength and maximum curvature along the body) are considered. We show that five segments are sufficient to describe the kinematics with at least 99% accuracy. For optimal performance, segments should progressively get shorter towards the tail. We also show that locations where bending moments are applied vary among species, possibly because of differences in morphology. More specifically, we find that wider fish have shorter head segments. We discover that once bending points are factored in, the kinematics differences observed in these species collapse into a single undulatory pattern. The amplitude and timing of how body segments move entirely depend on their respective joint positions along the body. Head and body segments are also coupled in a timely manner, which depends on the position of the most anterior joint. Our findings provide a mechanistic understanding of how morphology relates to kinematics and highlight the importance of head control, which is often overlooked in current robot designs.",
keywords = "Carangiform swimmers, Fish robots, Multi-segment model, Steady swimming, Undulatory kinematics",
author = "Fetherstonhaugh, {Samuel E.A.W.} and Qiang Shen and Otar Akanyeti",
note = "Funding Information: This manuscript is dedicated to the memory of Mr. Martin Nelmes. We thank Dr. Alexandros Giagkos for useful discussions during the implementation of the genetic algorithm. We also thank Melissa O{\textquoteright}Reilly and James Bradley Strong for commenting on the earlier version of the manuscript, and Allison Zwarycz for fish drawings in figure 4. This work is supported by S{\'e}r Cymru Cofund II Research Fellowship Grant to OA and QS and by Knowledge Economy Skills Scholarship to OA and SEAWF. Both Grants were provided by European Social Funds through the Welsh Government. Publisher Copyright: {\textcopyright} 2021 Institute of Physics Publishing. All rights reserved.",
year = "2021",
month = may,
day = "20",
doi = "10.1088/1748-3190/abf031",
language = "English",
volume = "16",
journal = "Bioinspiration & Biomimetics",
issn = "1748-3190",
publisher = "IOP Publishing",
number = "4",

}

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TY - JOUR

T1 - Automatic segmentation of fish midlines for optimizing robot design

AU - Fetherstonhaugh, Samuel E.A.W.

AU - Shen, Qiang

AU - Akanyeti, Otar

N1 - Funding Information: This manuscript is dedicated to the memory of Mr. Martin Nelmes. We thank Dr. Alexandros Giagkos for useful discussions during the implementation of the genetic algorithm. We also thank Melissa O’Reilly and James Bradley Strong for commenting on the earlier version of the manuscript, and Allison Zwarycz for fish drawings in figure 4. This work is supported by Sér Cymru Cofund II Research Fellowship Grant to OA and QS and by Knowledge Economy Skills Scholarship to OA and SEAWF. Both Grants were provided by European Social Funds through the Welsh Government. Publisher Copyright: © 2021 Institute of Physics Publishing. All rights reserved.

PY - 2021/5/20

Y1 - 2021/5/20

N2 - While fish use continuous and flexible bodies to propel themselves, fish robots are often made from interconnected segments. How many segments do robots need to represent fish movements accurately? We propose a new method to automatically determine parsimonious robot models from actual fish data. We first identify key bending points (i.e., joint positions) along the body and then study the concerted movement of the segments so that the difference between actual fish and modelled bending kinematics is minimized. To demonstrate the utility of our method, we analyse the steady swimming kinematics of 10 morphologically distinct fish species. Broadly classified as sub-carangiform (e.g., rainbow trout) and carangiform (e.g., crevalle jack) swimmers, these species exhibit variations in the way they undulate when traditional parameters (including head and tail beat amplitudes, body wavelength and maximum curvature along the body) are considered. We show that five segments are sufficient to describe the kinematics with at least 99% accuracy. For optimal performance, segments should progressively get shorter towards the tail. We also show that locations where bending moments are applied vary among species, possibly because of differences in morphology. More specifically, we find that wider fish have shorter head segments. We discover that once bending points are factored in, the kinematics differences observed in these species collapse into a single undulatory pattern. The amplitude and timing of how body segments move entirely depend on their respective joint positions along the body. Head and body segments are also coupled in a timely manner, which depends on the position of the most anterior joint. Our findings provide a mechanistic understanding of how morphology relates to kinematics and highlight the importance of head control, which is often overlooked in current robot designs.

AB - While fish use continuous and flexible bodies to propel themselves, fish robots are often made from interconnected segments. How many segments do robots need to represent fish movements accurately? We propose a new method to automatically determine parsimonious robot models from actual fish data. We first identify key bending points (i.e., joint positions) along the body and then study the concerted movement of the segments so that the difference between actual fish and modelled bending kinematics is minimized. To demonstrate the utility of our method, we analyse the steady swimming kinematics of 10 morphologically distinct fish species. Broadly classified as sub-carangiform (e.g., rainbow trout) and carangiform (e.g., crevalle jack) swimmers, these species exhibit variations in the way they undulate when traditional parameters (including head and tail beat amplitudes, body wavelength and maximum curvature along the body) are considered. We show that five segments are sufficient to describe the kinematics with at least 99% accuracy. For optimal performance, segments should progressively get shorter towards the tail. We also show that locations where bending moments are applied vary among species, possibly because of differences in morphology. More specifically, we find that wider fish have shorter head segments. We discover that once bending points are factored in, the kinematics differences observed in these species collapse into a single undulatory pattern. The amplitude and timing of how body segments move entirely depend on their respective joint positions along the body. Head and body segments are also coupled in a timely manner, which depends on the position of the most anterior joint. Our findings provide a mechanistic understanding of how morphology relates to kinematics and highlight the importance of head control, which is often overlooked in current robot designs.

KW - Carangiform swimmers

KW - Fish robots

KW - Multi-segment model

KW - Steady swimming

KW - Undulatory kinematics

UR - http://www.scopus.com/inward/record.url?scp=85106548999&partnerID=8YFLogxK

U2 - 10.1088/1748-3190/abf031

DO - 10.1088/1748-3190/abf031

M3 - Article

C2 - 33735844

AN - SCOPUS:85106548999

VL - 16

JO - Bioinspiration & Biomimetics

JF - Bioinspiration & Biomimetics

SN - 1748-3190

IS - 4

M1 - 046005

ER -

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