Loading…

Task allocation and path planning for collaborative AUVs operating through an underwater acoustic network

Multiple cooperative vehicles, joined in an acoustic communication network, can perform time-critical, cooperative operations given a robust task allocation mechanism and an efficient path planning model. In this paper, we present solutions for the task-allocation and path-planning problems of the c...

Full description

Saved in:
Bibliographic Details
Main Authors: Yueyue Deng, Beaujean, P, An, E, Carlson, E
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 9
container_issue
container_start_page 1
container_title
container_volume
creator Yueyue Deng
Beaujean, P
An, E
Carlson, E
description Multiple cooperative vehicles, joined in an acoustic communication network, can perform time-critical, cooperative operations given a robust task allocation mechanism and an efficient path planning model. In this paper, we present solutions for the task-allocation and path-planning problems of the cooperative schema for multiple AUVs: a Location-Aided task Allocation Framework (LAAF) algorithm for multi-target task assignment and the Grid-based Multi-Objective Optimal Programming (GMOOP) mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Our research is based on an existing mobile ad-hoc network underwater acoustic simulator and two routing protocols (blind flooding and dynamic source routing). The LAAF and GMOOP controllers combine within a "task-planact" structure to generate an optimized local system output in a timely manner to achieve fleet-wide cooperation. Our preliminary results demonstrate that the location-aided auction strategies perform significantly better than a generic auction algorithm in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path planning technique provides an efficient method for multi-objective tasks by cooperative agents with limited communication capabilities with its results can be referenced in [7]. Prior to this work, existing multi-objective action selection methods were limited to robust networks where constant, reliable communication was available. Both the LAAF and GMOOP algorithms were robust to poor acoustic network conditions and ongoing changing environments. LAAF dynamic task allocation and the GMOOP path planning controller provide an effective solution for cooperative search-classify missions with multiple AUVs under marginal communication conditions.
doi_str_mv 10.1109/OCEANS.2010.5664050
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5664050</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5664050</ieee_id><sourcerecordid>5664050</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-8e5763c15185038866a036ddbecfe07f623358f6d822543a74221efe7d800353</originalsourceid><addsrcrecordid>eNo1kM9OAjEYxGuURECegEtfYPFrv_49EoJiQuQgeiVltwsN63bTXSS-vWvE02Qmv5nDEDJlMGMM7ONmsZy_vs049IFUSoCEGzJiggshEFHckonV5t9zdkeGwKzONBo5ICMOYC1wtOqeTNo27IExBQyNHZKwde2JuqqKuetCrKmrC9q47kibytV1qA-0jInmsarcPqae-fJ0_v7R0tj4X9sD3THF8-HYV-m5Lny6uM4n6vJ4bruQ09p3l5hOD2RQuqr1k6uOyfZpuV2ssvXm-WUxX2eBadllxkutMGeSGQlojFIOUBXF3uelB10qjihNqQrDuRTotOCc-dLrwgCgxDGZ_s0G7_2uSeHTpe_d9TX8AdkrXaA</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Task allocation and path planning for collaborative AUVs operating through an underwater acoustic network</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Yueyue Deng ; Beaujean, P ; An, E ; Carlson, E</creator><creatorcontrib>Yueyue Deng ; Beaujean, P ; An, E ; Carlson, E</creatorcontrib><description>Multiple cooperative vehicles, joined in an acoustic communication network, can perform time-critical, cooperative operations given a robust task allocation mechanism and an efficient path planning model. In this paper, we present solutions for the task-allocation and path-planning problems of the cooperative schema for multiple AUVs: a Location-Aided task Allocation Framework (LAAF) algorithm for multi-target task assignment and the Grid-based Multi-Objective Optimal Programming (GMOOP) mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Our research is based on an existing mobile ad-hoc network underwater acoustic simulator and two routing protocols (blind flooding and dynamic source routing). The LAAF and GMOOP controllers combine within a "task-planact" structure to generate an optimized local system output in a timely manner to achieve fleet-wide cooperation. Our preliminary results demonstrate that the location-aided auction strategies perform significantly better than a generic auction algorithm in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path planning technique provides an efficient method for multi-objective tasks by cooperative agents with limited communication capabilities with its results can be referenced in [7]. Prior to this work, existing multi-objective action selection methods were limited to robust networks where constant, reliable communication was available. Both the LAAF and GMOOP algorithms were robust to poor acoustic network conditions and ongoing changing environments. LAAF dynamic task allocation and the GMOOP path planning controller provide an effective solution for cooperative search-classify missions with multiple AUVs under marginal communication conditions.</description><identifier>ISSN: 0197-7385</identifier><identifier>ISBN: 9781424443321</identifier><identifier>ISBN: 1424443326</identifier><identifier>EISBN: 1424443334</identifier><identifier>EISBN: 9781424443338</identifier><identifier>DOI: 10.1109/OCEANS.2010.5664050</identifier><identifier>LCCN: 2009902396</identifier><language>eng</language><publisher>IEEE</publisher><subject>Acoustics ; Classification algorithms ; Resource management ; Robot kinematics ; Robot sensing systems ; Vehicles</subject><ispartof>OCEANS 2010 MTS/IEEE SEATTLE, 2010, p.1-9</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5664050$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5664050$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yueyue Deng</creatorcontrib><creatorcontrib>Beaujean, P</creatorcontrib><creatorcontrib>An, E</creatorcontrib><creatorcontrib>Carlson, E</creatorcontrib><title>Task allocation and path planning for collaborative AUVs operating through an underwater acoustic network</title><title>OCEANS 2010 MTS/IEEE SEATTLE</title><addtitle>OCEANS</addtitle><description>Multiple cooperative vehicles, joined in an acoustic communication network, can perform time-critical, cooperative operations given a robust task allocation mechanism and an efficient path planning model. In this paper, we present solutions for the task-allocation and path-planning problems of the cooperative schema for multiple AUVs: a Location-Aided task Allocation Framework (LAAF) algorithm for multi-target task assignment and the Grid-based Multi-Objective Optimal Programming (GMOOP) mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Our research is based on an existing mobile ad-hoc network underwater acoustic simulator and two routing protocols (blind flooding and dynamic source routing). The LAAF and GMOOP controllers combine within a "task-planact" structure to generate an optimized local system output in a timely manner to achieve fleet-wide cooperation. Our preliminary results demonstrate that the location-aided auction strategies perform significantly better than a generic auction algorithm in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path planning technique provides an efficient method for multi-objective tasks by cooperative agents with limited communication capabilities with its results can be referenced in [7]. Prior to this work, existing multi-objective action selection methods were limited to robust networks where constant, reliable communication was available. Both the LAAF and GMOOP algorithms were robust to poor acoustic network conditions and ongoing changing environments. LAAF dynamic task allocation and the GMOOP path planning controller provide an effective solution for cooperative search-classify missions with multiple AUVs under marginal communication conditions.</description><subject>Acoustics</subject><subject>Classification algorithms</subject><subject>Resource management</subject><subject>Robot kinematics</subject><subject>Robot sensing systems</subject><subject>Vehicles</subject><issn>0197-7385</issn><isbn>9781424443321</isbn><isbn>1424443326</isbn><isbn>1424443334</isbn><isbn>9781424443338</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kM9OAjEYxGuURECegEtfYPFrv_49EoJiQuQgeiVltwsN63bTXSS-vWvE02Qmv5nDEDJlMGMM7ONmsZy_vs049IFUSoCEGzJiggshEFHckonV5t9zdkeGwKzONBo5ICMOYC1wtOqeTNo27IExBQyNHZKwde2JuqqKuetCrKmrC9q47kibytV1qA-0jInmsarcPqae-fJ0_v7R0tj4X9sD3THF8-HYV-m5Lny6uM4n6vJ4bruQ09p3l5hOD2RQuqr1k6uOyfZpuV2ssvXm-WUxX2eBadllxkutMGeSGQlojFIOUBXF3uelB10qjihNqQrDuRTotOCc-dLrwgCgxDGZ_s0G7_2uSeHTpe_d9TX8AdkrXaA</recordid><startdate>201009</startdate><enddate>201009</enddate><creator>Yueyue Deng</creator><creator>Beaujean, P</creator><creator>An, E</creator><creator>Carlson, E</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201009</creationdate><title>Task allocation and path planning for collaborative AUVs operating through an underwater acoustic network</title><author>Yueyue Deng ; Beaujean, P ; An, E ; Carlson, E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-8e5763c15185038866a036ddbecfe07f623358f6d822543a74221efe7d800353</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Acoustics</topic><topic>Classification algorithms</topic><topic>Resource management</topic><topic>Robot kinematics</topic><topic>Robot sensing systems</topic><topic>Vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yueyue Deng</creatorcontrib><creatorcontrib>Beaujean, P</creatorcontrib><creatorcontrib>An, E</creatorcontrib><creatorcontrib>Carlson, E</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yueyue Deng</au><au>Beaujean, P</au><au>An, E</au><au>Carlson, E</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Task allocation and path planning for collaborative AUVs operating through an underwater acoustic network</atitle><btitle>OCEANS 2010 MTS/IEEE SEATTLE</btitle><stitle>OCEANS</stitle><date>2010-09</date><risdate>2010</risdate><spage>1</spage><epage>9</epage><pages>1-9</pages><issn>0197-7385</issn><isbn>9781424443321</isbn><isbn>1424443326</isbn><eisbn>1424443334</eisbn><eisbn>9781424443338</eisbn><abstract>Multiple cooperative vehicles, joined in an acoustic communication network, can perform time-critical, cooperative operations given a robust task allocation mechanism and an efficient path planning model. In this paper, we present solutions for the task-allocation and path-planning problems of the cooperative schema for multiple AUVs: a Location-Aided task Allocation Framework (LAAF) algorithm for multi-target task assignment and the Grid-based Multi-Objective Optimal Programming (GMOOP) mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Our research is based on an existing mobile ad-hoc network underwater acoustic simulator and two routing protocols (blind flooding and dynamic source routing). The LAAF and GMOOP controllers combine within a "task-planact" structure to generate an optimized local system output in a timely manner to achieve fleet-wide cooperation. Our preliminary results demonstrate that the location-aided auction strategies perform significantly better than a generic auction algorithm in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path planning technique provides an efficient method for multi-objective tasks by cooperative agents with limited communication capabilities with its results can be referenced in [7]. Prior to this work, existing multi-objective action selection methods were limited to robust networks where constant, reliable communication was available. Both the LAAF and GMOOP algorithms were robust to poor acoustic network conditions and ongoing changing environments. LAAF dynamic task allocation and the GMOOP path planning controller provide an effective solution for cooperative search-classify missions with multiple AUVs under marginal communication conditions.</abstract><pub>IEEE</pub><doi>10.1109/OCEANS.2010.5664050</doi><tpages>9</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0197-7385
ispartof OCEANS 2010 MTS/IEEE SEATTLE, 2010, p.1-9
issn 0197-7385
language eng
recordid cdi_ieee_primary_5664050
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Acoustics
Classification algorithms
Resource management
Robot kinematics
Robot sensing systems
Vehicles
title Task allocation and path planning for collaborative AUVs operating through an underwater acoustic network
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T21%3A15%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Task%20allocation%20and%20path%20planning%20for%20collaborative%20AUVs%20operating%20through%20an%20underwater%20acoustic%20network&rft.btitle=OCEANS%202010%20MTS/IEEE%20SEATTLE&rft.au=Yueyue%20Deng&rft.date=2010-09&rft.spage=1&rft.epage=9&rft.pages=1-9&rft.issn=0197-7385&rft.isbn=9781424443321&rft.isbn_list=1424443326&rft_id=info:doi/10.1109/OCEANS.2010.5664050&rft.eisbn=1424443334&rft.eisbn_list=9781424443338&rft_dat=%3Cieee_6IE%3E5664050%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i175t-8e5763c15185038866a036ddbecfe07f623358f6d822543a74221efe7d800353%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5664050&rfr_iscdi=true