## Journal article: Artificial lateral line based relative state estimation between an upstream oscillating fin and a downstream robotic fish

No Thumbnail Available
##### Files
There are no files associated with this item.
2021
Zheng, Xingwen
Wang, Wei
Xie, Guangming
Journal article
Published
##### Abstract
The lateral line enables fish to efficiently sense the surrounding environment, thus assisting flow-related fish behaviors. Inspired by this phenomenon, varieties of artificial lateral line systems (ALLSs) have been developed and applied to underwater robots. This article focuses on using the pressure sensor arrays based ALLS-measured hydrodynamic pressure variations (HPVs) for estimating the relative states between an upstream oscillating fin and a downstream robotic fish. The HPVs and relative states are measured in flume experiments in which the oscillating fin and the robotic fish have been locate with upstream-downstream formation in a flume. The relative states include the relative oscillating frequency, amplitude, and offset of the upstream oscillating fin to the downstream robotic fish, the relative vertical distance, the relative yaw angle, the relative pitch angle, and the relative roll angle between the upstream oscillating fin and the downstream robotic fish. Regression models between the ALLS-measured and the mentioned relative states are investigated, and regression models-based relative state estimations are conducted. Specifically, two criteria are proposed firstly to investigate not only the sensitivity of each pressure sensor to the variations of relative state but also the insufficiency and redundancy of the pressure sensors. And thus the pressure sensors used for regression analysis are determined. Then four typical regression methods, including random forest (RF) algorithm, support vector regression, back propagation neural network, and multiple linear regression method are used for establishing regression models between the ALLS-measured HPVs and the relative states. Then regression effects of the four methods are compared and discussed. Finally, the RF-based method, which has the best regression effect, is used to estimate the relative yaw angle and oscillating amplitude using the ALLS-measured HPVs and exhibits excellent estimation performance.
##### Subject (DDC)
570 Biosciences, Biology
##### Published in
Bioinspiration & Biomimetics ; 16 (2021), 1. - 016012. - Institute of Physics Publishing (IOP). - ISSN 1748-3182. - eISSN 1748-3190
##### Cite This
ISO 690ZHENG, Xingwen, Wei WANG, Liang LI, Guangming XIE, 2021. Artificial lateral line based relative state estimation between an upstream oscillating fin and a downstream robotic fish. In: Bioinspiration & Biomimetics. Institute of Physics Publishing (IOP). 16(1), 016012. ISSN 1748-3182. eISSN 1748-3190. Available under: doi: 10.1088/1748-3190/abb86c
BibTex
@article{Zheng2021Artif-52264,
year={2021},
doi={10.1088/1748-3190/abb86c},
title={Artificial lateral line based relative state estimation between an upstream oscillating fin and a downstream robotic fish},
number={1},
volume={16},
issn={1748-3182},
journal={Bioinspiration & Biomimetics},
author={Zheng, Xingwen and Wang, Wei and Li, Liang and Xie, Guangming},
note={Article Number: 016012}
}

RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<dc:language>eng</dc:language>
<dc:contributor>Zheng, Xingwen</dc:contributor>
<dcterms:title>Artificial lateral line based relative state estimation between an upstream oscillating fin and a downstream robotic fish</dcterms:title>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
<dc:creator>Zheng, Xingwen</dc:creator>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43615"/>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dc:creator>Xie, Guangming</dc:creator>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-01-04T12:12:21Z</dcterms:available>
<dc:creator>Li, Liang</dc:creator>
<dcterms:issued>2021</dcterms:issued>
<dc:creator>Wang, Wei</dc:creator>
<dcterms:abstract xml:lang="eng">The lateral line enables fish to efficiently sense the surrounding environment, thus assisting flow-related fish behaviors. Inspired by this phenomenon, varieties of artificial lateral line systems (ALLSs) have been developed and applied to underwater robots. This article focuses on using the pressure sensor arrays based ALLS-measured hydrodynamic pressure variations (HPVs) for estimating the relative states between an upstream oscillating fin and a downstream robotic fish. The HPVs and relative states are measured in flume experiments in which the oscillating fin and the robotic fish have been locate with upstream-downstream formation in a flume. The relative states include the relative oscillating frequency, amplitude, and offset of the upstream oscillating fin to the downstream robotic fish, the relative vertical distance, the relative yaw angle, the relative pitch angle, and the relative roll angle between the upstream oscillating fin and the downstream robotic fish. Regression models between the ALLS-measured and the mentioned relative states are investigated, and regression models-based relative state estimations are conducted. Specifically, two criteria are proposed firstly to investigate not only the sensitivity of each pressure sensor to the variations of relative state but also the insufficiency and redundancy of the pressure sensors. And thus the pressure sensors used for regression analysis are determined. Then four typical regression methods, including random forest (RF) algorithm, support vector regression, back propagation neural network, and multiple linear regression method are used for establishing regression models between the ALLS-measured HPVs and the relative states. Then regression effects of the four methods are compared and discussed. Finally, the RF-based method, which has the best regression effect, is used to estimate the relative yaw angle and oscillating amplitude using the ALLS-measured HPVs and exhibits excellent estimation performance.</dcterms:abstract>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-01-04T12:12:21Z</dc:date>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43615"/>
<dc:contributor>Wang, Wei</dc:contributor>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/52264"/>
<dc:contributor>Xie, Guangming</dc:contributor>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:contributor>Li, Liang</dc:contributor>
</rdf:Description>
</rdf:RDF>

Yes