Loading…
Intelligent autonomy for unmanned surface and underwater vehicles
As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic syst...
Saved in:
Main Authors: | , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c141t-9250560535ffefc739ef1e50e6ba32bed35f50821906bf1fac0319ed688d71643 |
---|---|
cites | |
container_end_page | 10 |
container_issue | |
container_start_page | 1 |
container_title | |
container_volume | |
creator | Huntsberger, T. Woodward, G. |
description | As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decision-making, which would otherwise be performed by human operators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented. |
doi_str_mv | 10.23919/OCEANS.2011.6107312 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6107312</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6107312</ieee_id><sourcerecordid>6107312</sourcerecordid><originalsourceid>FETCH-LOGICAL-c141t-9250560535ffefc739ef1e50e6ba32bed35f50821906bf1fac0319ed688d71643</originalsourceid><addsrcrecordid>eNotUM1KxDAYjKjguvYJ9JAX6Jovaf6Opay6sLgH9bykzRcttKmkrbJvb8E9DcwwPwwhD8A2XFiwj4dqW76-bTgD2ChgWgC_IJnVhlkhrNTCmktyC4XUGgqu-RVZMbA618LIG5KNY1svVsVAGLsi5S5O2HXtJ8aJunka4tCfaBgSnWPvYkRPxzkF1yB10S-kx_TrJkz0B7_apsPxjlwH142YnXFNPp6279VLvj8876pynzdQwJRbLplUTAoZAoZmmYkBUDJUtRO8Rr8IkhkOlqk6wNLIBFj0yhivQRViTe7_c1tEPH6ntnfpdDw_IP4At-1OGA</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Intelligent autonomy for unmanned surface and underwater vehicles</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Huntsberger, T. ; Woodward, G.</creator><creatorcontrib>Huntsberger, T. ; Woodward, G.</creatorcontrib><description>As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decision-making, which would otherwise be performed by human operators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.</description><identifier>ISSN: 0197-7385</identifier><identifier>ISBN: 1457714272</identifier><identifier>ISBN: 9781457714276</identifier><identifier>EISBN: 9780933957398</identifier><identifier>EISBN: 0933957394</identifier><identifier>DOI: 10.23919/OCEANS.2011.6107312</identifier><language>eng</language><publisher>IEEE</publisher><subject>benthic habitat monitoring ; Engines ; environmental sensing ; Hazards ; maritime autonomy ; Navigation ; onboard planning/re-planning ; Planning ; Real time systems ; Vehicle dynamics ; Vehicles</subject><ispartof>OCEANS'11 MTS/IEEE KONA, 2011, p.1-10</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c141t-9250560535ffefc739ef1e50e6ba32bed35f50821906bf1fac0319ed688d71643</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6107312$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,27924,54919</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6107312$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Huntsberger, T.</creatorcontrib><creatorcontrib>Woodward, G.</creatorcontrib><title>Intelligent autonomy for unmanned surface and underwater vehicles</title><title>OCEANS'11 MTS/IEEE KONA</title><addtitle>OCEANS</addtitle><description>As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decision-making, which would otherwise be performed by human operators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.</description><subject>benthic habitat monitoring</subject><subject>Engines</subject><subject>environmental sensing</subject><subject>Hazards</subject><subject>maritime autonomy</subject><subject>Navigation</subject><subject>onboard planning/re-planning</subject><subject>Planning</subject><subject>Real time systems</subject><subject>Vehicle dynamics</subject><subject>Vehicles</subject><issn>0197-7385</issn><isbn>1457714272</isbn><isbn>9781457714276</isbn><isbn>9780933957398</isbn><isbn>0933957394</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotUM1KxDAYjKjguvYJ9JAX6Jovaf6Opay6sLgH9bykzRcttKmkrbJvb8E9DcwwPwwhD8A2XFiwj4dqW76-bTgD2ChgWgC_IJnVhlkhrNTCmktyC4XUGgqu-RVZMbA618LIG5KNY1svVsVAGLsi5S5O2HXtJ8aJunka4tCfaBgSnWPvYkRPxzkF1yB10S-kx_TrJkz0B7_apsPxjlwH142YnXFNPp6279VLvj8876pynzdQwJRbLplUTAoZAoZmmYkBUDJUtRO8Rr8IkhkOlqk6wNLIBFj0yhivQRViTe7_c1tEPH6ntnfpdDw_IP4At-1OGA</recordid><startdate>201109</startdate><enddate>201109</enddate><creator>Huntsberger, T.</creator><creator>Woodward, G.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201109</creationdate><title>Intelligent autonomy for unmanned surface and underwater vehicles</title><author>Huntsberger, T. ; Woodward, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c141t-9250560535ffefc739ef1e50e6ba32bed35f50821906bf1fac0319ed688d71643</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>benthic habitat monitoring</topic><topic>Engines</topic><topic>environmental sensing</topic><topic>Hazards</topic><topic>maritime autonomy</topic><topic>Navigation</topic><topic>onboard planning/re-planning</topic><topic>Planning</topic><topic>Real time systems</topic><topic>Vehicle dynamics</topic><topic>Vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huntsberger, T.</creatorcontrib><creatorcontrib>Woodward, G.</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>Huntsberger, T.</au><au>Woodward, G.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Intelligent autonomy for unmanned surface and underwater vehicles</atitle><btitle>OCEANS'11 MTS/IEEE KONA</btitle><stitle>OCEANS</stitle><date>2011-09</date><risdate>2011</risdate><spage>1</spage><epage>10</epage><pages>1-10</pages><issn>0197-7385</issn><isbn>1457714272</isbn><isbn>9781457714276</isbn><eisbn>9780933957398</eisbn><eisbn>0933957394</eisbn><abstract>As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decision-making, which would otherwise be performed by human operators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.</abstract><pub>IEEE</pub><doi>10.23919/OCEANS.2011.6107312</doi><tpages>10</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 0197-7385 |
ispartof | OCEANS'11 MTS/IEEE KONA, 2011, p.1-10 |
issn | 0197-7385 |
language | eng |
recordid | cdi_ieee_primary_6107312 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | benthic habitat monitoring Engines environmental sensing Hazards maritime autonomy Navigation onboard planning/re-planning Planning Real time systems Vehicle dynamics Vehicles |
title | Intelligent autonomy for unmanned surface and underwater vehicles |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T20%3A51%3A06IST&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=Intelligent%20autonomy%20for%20unmanned%20surface%20and%20underwater%20vehicles&rft.btitle=OCEANS'11%20MTS/IEEE%20KONA&rft.au=Huntsberger,%20T.&rft.date=2011-09&rft.spage=1&rft.epage=10&rft.pages=1-10&rft.issn=0197-7385&rft.isbn=1457714272&rft.isbn_list=9781457714276&rft_id=info:doi/10.23919/OCEANS.2011.6107312&rft.eisbn=9780933957398&rft.eisbn_list=0933957394&rft_dat=%3Cieee_6IE%3E6107312%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c141t-9250560535ffefc739ef1e50e6ba32bed35f50821906bf1fac0319ed688d71643%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=6107312&rfr_iscdi=true |