Approximate representations for multi-robot control policies that maximize mutual information

We address the problem of controlling a small team of robots to estimate the location of a mobile target using non-linear range-only sensors. Our control law maximizes the mutual information between the team’s estimate and future measurements over a finite time horizon. Because the computations asso...

Full description

Saved in:
Bibliographic Details
Published in:Autonomous robots 2014-12, Vol.37 (4), p.383-400
Main Authors: Charrow, Benjamin, Kumar, Vijay, Michael, Nathan
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Artificial Intelligence
Computer Imaging
Control
Engineering
Estimates
Mathematical analysis
Mechatronics
Multiple robots
Pattern Recognition and Graphics
Policies
Representations
Robotics
Robotics and Automation
Robots
Vision
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c452t-ead87bfda947b0b6e61442ff9d0e275bc7738eaacb47b96d793b3c26ebba7a703
cites cdi_FETCH-LOGICAL-c452t-ead87bfda947b0b6e61442ff9d0e275bc7738eaacb47b96d793b3c26ebba7a703
container_end_page 400
container_issue 4
container_start_page 383
container_title Autonomous robots
container_volume 37
creator Charrow, Benjamin
Kumar, Vijay
Michael, Nathan
description We address the problem of controlling a small team of robots to estimate the location of a mobile target using non-linear range-only sensors. Our control law maximizes the mutual information between the team’s estimate and future measurements over a finite time horizon. Because the computations associated with such policies scale poorly with the number of robots, the time horizon associated with the policy, and typical non-parametric representations of the belief, we design approximate representations that enable real-time operation. The main contributions of this paper include the control policy, an algorithm for approximating the belief state, and an extensive study of the performance of these algorithms using simulations and real world experiments in complex, indoor environments.
doi_str_mv 10.1007/s10514-014-9411-2
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1651396734</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3467757461</sourcerecordid><originalsourceid>FETCH-LOGICAL-c452t-ead87bfda947b0b6e61442ff9d0e275bc7738eaacb47b96d793b3c26ebba7a703</originalsourceid><addsrcrecordid>eNp1kE1LxDAQhoMouH78AG8BL16qk7RpNsdl8QsWvOhRQtJOtUvb1CQF9debtR5E8BDmkOd5mXkJOWNwyQDkVWAgWJFBeqpgLON7ZMGEzDMpuNwnC1BcZUKo_JAchbAFACUBFuR5NY7evbe9iUg9jh4DDtHE1g2BNs7Tfupim3lnXaSVG6J3HR1d11YtBhpfTaS9SXr7iQmNk-loOySv_444IQeN6QKe_sxj8nRz_bi-yzYPt_fr1SarCsFjhqZeStvURhXSgi2xZEXBm0bVgFwKW0mZL9GYyqZ_VdZS5TaveInWGmkk5MfkYs5Nt7xNGKLu21Bh15kB3RQ0KwXLVSnzIqHnf9Ctm_yQtksUKxSUjPFEsZmqvAvBY6NHnzryH5qB3hWu58J1KlzvCtc7h89OSOzwgv5X8r_SF4R9haw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1614906112</pqid></control><display><type>article</type><title>Approximate representations for multi-robot control policies that maximize mutual information</title><source>Springer Nature</source><creator>Charrow, Benjamin ; Kumar, Vijay ; Michael, Nathan</creator><creatorcontrib>Charrow, Benjamin ; Kumar, Vijay ; Michael, Nathan</creatorcontrib><description>We address the problem of controlling a small team of robots to estimate the location of a mobile target using non-linear range-only sensors. Our control law maximizes the mutual information between the team’s estimate and future measurements over a finite time horizon. Because the computations associated with such policies scale poorly with the number of robots, the time horizon associated with the policy, and typical non-parametric representations of the belief, we design approximate representations that enable real-time operation. The main contributions of this paper include the control policy, an algorithm for approximating the belief state, and an extensive study of the performance of these algorithms using simulations and real world experiments in complex, indoor environments.</description><identifier>ISSN: 0929-5593</identifier><identifier>EISSN: 1573-7527</identifier><identifier>DOI: 10.1007/s10514-014-9411-2</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Algorithms ; Approximation ; Artificial Intelligence ; Computer Imaging ; Control ; Engineering ; Estimates ; Mathematical analysis ; Mechatronics ; Multiple robots ; Pattern Recognition and Graphics ; Policies ; Representations ; Robotics ; Robotics and Automation ; Robots ; Vision</subject><ispartof>Autonomous robots, 2014-12, Vol.37 (4), p.383-400</ispartof><rights>Springer Science+Business Media New York 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c452t-ead87bfda947b0b6e61442ff9d0e275bc7738eaacb47b96d793b3c26ebba7a703</citedby><cites>FETCH-LOGICAL-c452t-ead87bfda947b0b6e61442ff9d0e275bc7738eaacb47b96d793b3c26ebba7a703</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Charrow, Benjamin</creatorcontrib><creatorcontrib>Kumar, Vijay</creatorcontrib><creatorcontrib>Michael, Nathan</creatorcontrib><title>Approximate representations for multi-robot control policies that maximize mutual information</title><title>Autonomous robots</title><addtitle>Auton Robot</addtitle><description>We address the problem of controlling a small team of robots to estimate the location of a mobile target using non-linear range-only sensors. Our control law maximizes the mutual information between the team’s estimate and future measurements over a finite time horizon. Because the computations associated with such policies scale poorly with the number of robots, the time horizon associated with the policy, and typical non-parametric representations of the belief, we design approximate representations that enable real-time operation. The main contributions of this paper include the control policy, an algorithm for approximating the belief state, and an extensive study of the performance of these algorithms using simulations and real world experiments in complex, indoor environments.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>Artificial Intelligence</subject><subject>Computer Imaging</subject><subject>Control</subject><subject>Engineering</subject><subject>Estimates</subject><subject>Mathematical analysis</subject><subject>Mechatronics</subject><subject>Multiple robots</subject><subject>Pattern Recognition and Graphics</subject><subject>Policies</subject><subject>Representations</subject><subject>Robotics</subject><subject>Robotics and Automation</subject><subject>Robots</subject><subject>Vision</subject><issn>0929-5593</issn><issn>1573-7527</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp1kE1LxDAQhoMouH78AG8BL16qk7RpNsdl8QsWvOhRQtJOtUvb1CQF9debtR5E8BDmkOd5mXkJOWNwyQDkVWAgWJFBeqpgLON7ZMGEzDMpuNwnC1BcZUKo_JAchbAFACUBFuR5NY7evbe9iUg9jh4DDtHE1g2BNs7Tfupim3lnXaSVG6J3HR1d11YtBhpfTaS9SXr7iQmNk-loOySv_444IQeN6QKe_sxj8nRz_bi-yzYPt_fr1SarCsFjhqZeStvURhXSgi2xZEXBm0bVgFwKW0mZL9GYyqZ_VdZS5TaveInWGmkk5MfkYs5Nt7xNGKLu21Bh15kB3RQ0KwXLVSnzIqHnf9Ctm_yQtksUKxSUjPFEsZmqvAvBY6NHnzryH5qB3hWu58J1KlzvCtc7h89OSOzwgv5X8r_SF4R9haw</recordid><startdate>20141201</startdate><enddate>20141201</enddate><creator>Charrow, Benjamin</creator><creator>Kumar, Vijay</creator><creator>Michael, Nathan</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>S0W</scope></search><sort><creationdate>20141201</creationdate><title>Approximate representations for multi-robot control policies that maximize mutual information</title><author>Charrow, Benjamin ; Kumar, Vijay ; Michael, Nathan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c452t-ead87bfda947b0b6e61442ff9d0e275bc7738eaacb47b96d793b3c26ebba7a703</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Approximation</topic><topic>Artificial Intelligence</topic><topic>Computer Imaging</topic><topic>Control</topic><topic>Engineering</topic><topic>Estimates</topic><topic>Mathematical analysis</topic><topic>Mechatronics</topic><topic>Multiple robots</topic><topic>Pattern Recognition and Graphics</topic><topic>Policies</topic><topic>Representations</topic><topic>Robotics</topic><topic>Robotics and Automation</topic><topic>Robots</topic><topic>Vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Charrow, Benjamin</creatorcontrib><creatorcontrib>Kumar, Vijay</creatorcontrib><creatorcontrib>Michael, Nathan</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Engineering Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>DELNET Engineering &amp; Technology Collection</collection><jtitle>Autonomous robots</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Charrow, Benjamin</au><au>Kumar, Vijay</au><au>Michael, Nathan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Approximate representations for multi-robot control policies that maximize mutual information</atitle><jtitle>Autonomous robots</jtitle><stitle>Auton Robot</stitle><date>2014-12-01</date><risdate>2014</risdate><volume>37</volume><issue>4</issue><spage>383</spage><epage>400</epage><pages>383-400</pages><issn>0929-5593</issn><eissn>1573-7527</eissn><abstract>We address the problem of controlling a small team of robots to estimate the location of a mobile target using non-linear range-only sensors. Our control law maximizes the mutual information between the team’s estimate and future measurements over a finite time horizon. Because the computations associated with such policies scale poorly with the number of robots, the time horizon associated with the policy, and typical non-parametric representations of the belief, we design approximate representations that enable real-time operation. The main contributions of this paper include the control policy, an algorithm for approximating the belief state, and an extensive study of the performance of these algorithms using simulations and real world experiments in complex, indoor environments.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s10514-014-9411-2</doi><tpages>18</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0929-5593
ispartof Autonomous robots, 2014-12, Vol.37 (4), p.383-400
issn 0929-5593
1573-7527
language eng
recordid cdi_proquest_miscellaneous_1651396734
source Springer Nature
subjects Algorithms
Approximation
Artificial Intelligence
Computer Imaging
Control
Engineering
Estimates
Mathematical analysis
Mechatronics
Multiple robots
Pattern Recognition and Graphics
Policies
Representations
Robotics
Robotics and Automation
Robots
Vision
title Approximate representations for multi-robot control policies that maximize mutual information
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T08%3A53%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Approximate%20representations%20for%20multi-robot%20control%20policies%20that%20maximize%20mutual%20information&rft.jtitle=Autonomous%20robots&rft.au=Charrow,%20Benjamin&rft.date=2014-12-01&rft.volume=37&rft.issue=4&rft.spage=383&rft.epage=400&rft.pages=383-400&rft.issn=0929-5593&rft.eissn=1573-7527&rft_id=info:doi/10.1007/s10514-014-9411-2&rft_dat=%3Cproquest_cross%3E3467757461%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c452t-ead87bfda947b0b6e61442ff9d0e275bc7738eaacb47b96d793b3c26ebba7a703%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1614906112&rft_id=info:pmid/&rfr_iscdi=true