3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization

Water quality mapping for critical parameters such as temperature, salinity, and turbidity is crucial for assessing an aquaculture farm's health and yield capacity. Traditional approaches involve using boats or human divers, which are time-constrained and lack depth variability. This work prese...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Joshi, Kaustubh, Liu, Tianchen, Williams, Alan, Gray, Matthew, Lin, Xiaomin, Chopra, Nikhil
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Joshi, Kaustubh
Liu, Tianchen
Williams, Alan
Gray, Matthew
Lin, Xiaomin
Chopra, Nikhil
description Water quality mapping for critical parameters such as temperature, salinity, and turbidity is crucial for assessing an aquaculture farm's health and yield capacity. Traditional approaches involve using boats or human divers, which are time-constrained and lack depth variability. This work presents an innovative approach to 3D water quality mapping in shallow water environments using a BlueROV2 equipped with GPS and a water quality sensor. This system allows for accurate location correction by resurfacing when errors occur. This study is being conducted at an oyster farm in the Chesapeake Bay, USA, providing a more comprehensive and precise water quality analysis in aquaculture settings.
doi_str_mv 10.48550/arxiv.2409.11578
format Article
fullrecord <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2409_11578</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2409_11578</sourcerecordid><originalsourceid>FETCH-arxiv_primary_2409_115783</originalsourceid><addsrcrecordid>eNqFjr0OgjAUhbs4GPUBnLwvIIJAxFkhGnXQaBzJVYq5SWlJKQg-vUDcXc4Zzk8-xqaObXmB79sL1DVV1tKz15bj-KtgyBJ3C3c0XMO5REGmgRPmOckXlEWne1mhJpQGwtpwmfAEDigylBCRaGddJ1Uabm2k3_3RRT2UgaN6tn8fNKTkmA1SFAWf_HzEZlF43ezmPU-ca8pQN3HHFfdc7v_GF2lbRAg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization</title><source>arXiv.org</source><creator>Joshi, Kaustubh ; Liu, Tianchen ; Williams, Alan ; Gray, Matthew ; Lin, Xiaomin ; Chopra, Nikhil</creator><creatorcontrib>Joshi, Kaustubh ; Liu, Tianchen ; Williams, Alan ; Gray, Matthew ; Lin, Xiaomin ; Chopra, Nikhil</creatorcontrib><description>Water quality mapping for critical parameters such as temperature, salinity, and turbidity is crucial for assessing an aquaculture farm's health and yield capacity. Traditional approaches involve using boats or human divers, which are time-constrained and lack depth variability. This work presents an innovative approach to 3D water quality mapping in shallow water environments using a BlueROV2 equipped with GPS and a water quality sensor. This system allows for accurate location correction by resurfacing when errors occur. This study is being conducted at an oyster farm in the Chesapeake Bay, USA, providing a more comprehensive and precise water quality analysis in aquaculture settings.</description><identifier>DOI: 10.48550/arxiv.2409.11578</identifier><language>eng</language><subject>Computer Science - Robotics</subject><creationdate>2024-09</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2409.11578$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2409.11578$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Joshi, Kaustubh</creatorcontrib><creatorcontrib>Liu, Tianchen</creatorcontrib><creatorcontrib>Williams, Alan</creatorcontrib><creatorcontrib>Gray, Matthew</creatorcontrib><creatorcontrib>Lin, Xiaomin</creatorcontrib><creatorcontrib>Chopra, Nikhil</creatorcontrib><title>3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization</title><description>Water quality mapping for critical parameters such as temperature, salinity, and turbidity is crucial for assessing an aquaculture farm's health and yield capacity. Traditional approaches involve using boats or human divers, which are time-constrained and lack depth variability. This work presents an innovative approach to 3D water quality mapping in shallow water environments using a BlueROV2 equipped with GPS and a water quality sensor. This system allows for accurate location correction by resurfacing when errors occur. This study is being conducted at an oyster farm in the Chesapeake Bay, USA, providing a more comprehensive and precise water quality analysis in aquaculture settings.</description><subject>Computer Science - Robotics</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNqFjr0OgjAUhbs4GPUBnLwvIIJAxFkhGnXQaBzJVYq5SWlJKQg-vUDcXc4Zzk8-xqaObXmB79sL1DVV1tKz15bj-KtgyBJ3C3c0XMO5REGmgRPmOckXlEWne1mhJpQGwtpwmfAEDigylBCRaGddJ1Uabm2k3_3RRT2UgaN6tn8fNKTkmA1SFAWf_HzEZlF43ezmPU-ca8pQN3HHFfdc7v_GF2lbRAg</recordid><startdate>20240917</startdate><enddate>20240917</enddate><creator>Joshi, Kaustubh</creator><creator>Liu, Tianchen</creator><creator>Williams, Alan</creator><creator>Gray, Matthew</creator><creator>Lin, Xiaomin</creator><creator>Chopra, Nikhil</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20240917</creationdate><title>3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization</title><author>Joshi, Kaustubh ; Liu, Tianchen ; Williams, Alan ; Gray, Matthew ; Lin, Xiaomin ; Chopra, Nikhil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_2409_115783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Computer Science - Robotics</topic><toplevel>online_resources</toplevel><creatorcontrib>Joshi, Kaustubh</creatorcontrib><creatorcontrib>Liu, Tianchen</creatorcontrib><creatorcontrib>Williams, Alan</creatorcontrib><creatorcontrib>Gray, Matthew</creatorcontrib><creatorcontrib>Lin, Xiaomin</creatorcontrib><creatorcontrib>Chopra, Nikhil</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Joshi, Kaustubh</au><au>Liu, Tianchen</au><au>Williams, Alan</au><au>Gray, Matthew</au><au>Lin, Xiaomin</au><au>Chopra, Nikhil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization</atitle><date>2024-09-17</date><risdate>2024</risdate><abstract>Water quality mapping for critical parameters such as temperature, salinity, and turbidity is crucial for assessing an aquaculture farm's health and yield capacity. Traditional approaches involve using boats or human divers, which are time-constrained and lack depth variability. This work presents an innovative approach to 3D water quality mapping in shallow water environments using a BlueROV2 equipped with GPS and a water quality sensor. This system allows for accurate location correction by resurfacing when errors occur. This study is being conducted at an oyster farm in the Chesapeake Bay, USA, providing a more comprehensive and precise water quality analysis in aquaculture settings.</abstract><doi>10.48550/arxiv.2409.11578</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier DOI: 10.48550/arxiv.2409.11578
ispartof
issn
language eng
recordid cdi_arxiv_primary_2409_11578
source arXiv.org
subjects Computer Science - Robotics
title 3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T00%3A47%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=3D%20Water%20Quality%20Mapping%20using%20Invariant%20Extended%20Kalman%20Filtering%20for%20Underwater%20Robot%20Localization&rft.au=Joshi,%20Kaustubh&rft.date=2024-09-17&rft_id=info:doi/10.48550/arxiv.2409.11578&rft_dat=%3Carxiv_GOX%3E2409_11578%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true