A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation

A new ant algorithm for robot path planning is presented according to the latest achievements of research on actual ants. In this algorithm, m scout ants collaborate with each other to search for an optimal or near-optimal path. Of m scout ants, n ants adopt nearest-neighbor search strategy and the...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Qingbao Zhu, Lingling Wang
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Ant algorithm Collaboration Convergence Cooperation Mathematics Meeting planning Mobile robot Mobile robots Navigation Orbital robotics Path planning Robot kinematics Scout ant Space technology
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page	449
container_issue
container_start_page	444
container_title
container_volume	7
creator	Qingbao Zhu Lingling Wang
description	A new ant algorithm for robot path planning is presented according to the latest achievements of research on actual ants. In this algorithm, m scout ants collaborate with each other to search for an optimal or near-optimal path. Of m scout ants, n ants adopt nearest-neighbor search strategy and the left q=m-n ants adopt random search strategy. A section of optimal path will be found after all ants search L steps. Then m ants regard the end point of as the new starting point and search for L steps to find the next section of optimal path . Repeat this process until one of m ants reaches the goal. In this way, the path is consisted of h sections of path with step length L. Carry out the next generation search after step length L is modified, then repeat the searching course mentioned above. An optimal or near-optimal path will be found through comparison after multi-generation of searching. The simulation experiment results show that an optimal or near-optimal path can be planned even in environment with very complex obstacles, which can meet the requirements of real-time planning or navigation. The effect is quite satisfying.
doi_str_mv	10.1109/ICNC.2008.185
format	Conference Proceeding
fullrecord	<record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_4668017</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4668017</ieee_id><sourcerecordid>4668017</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-27c341e6798b82a936c172d04219a5865d5c620375d0f3cb26ecd3b2d7366a323</originalsourceid><addsrcrecordid>eNotzE9LwzAYgPGADpyzR09e8gVa3yRN3uRYi5uDMYd_ziNt0y3SJaONiN9eRE_P5cdDyC2DgjEw9-t6WxccQBdMywuSGdSAykghoDSXZM6ZxNxIKWfk-pcZKJnmVySbpg8AEAwRwczJsqJb90Wr4RBHn44n2seRvsQmJrqz6Uh3gw3BhwN9sJPraAz0tY2fiVYh0TrGsxtt8jHckFlvh8ll_12Q9-XjW_2Ub55X67ra5J6hTDnHVpTMKTS60dwaoVqGvIOSM2OlVrKTreIgUHbQi7bhyrWdaHiHQikruFiQu7-vd87tz6M_2fF7XyqlgaH4AdPES10</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Qingbao Zhu ; Lingling Wang</creator><creatorcontrib>Qingbao Zhu ; Lingling Wang</creatorcontrib><description>A new ant algorithm for robot path planning is presented according to the latest achievements of research on actual ants. In this algorithm, m scout ants collaborate with each other to search for an optimal or near-optimal path. Of m scout ants, n ants adopt nearest-neighbor search strategy and the left q=m-n ants adopt random search strategy. A section of optimal path will be found after all ants search L steps. Then m ants regard the end point of as the new starting point and search for L steps to find the next section of optimal path . Repeat this process until one of m ants reaches the goal. In this way, the path is consisted of h sections of path with step length L. Carry out the next generation search after step length L is modified, then repeat the searching course mentioned above. An optimal or near-optimal path will be found through comparison after multi-generation of searching. The simulation experiment results show that an optimal or near-optimal path can be planned even in environment with very complex obstacles, which can meet the requirements of real-time planning or navigation. The effect is quite satisfying.</description><identifier>ISSN: 2157-9555</identifier><identifier>ISBN: 9780769533049</identifier><identifier>ISBN: 0769533043</identifier><identifier>DOI: 10.1109/ICNC.2008.185</identifier><identifier>LCCN: 2008904182</identifier><language>eng</language><publisher>IEEE</publisher><subject>Ant algorithm ; Collaboration ; Convergence ; Cooperation ; Mathematics ; Meeting planning ; Mobile robot ; Mobile robots ; Navigation ; Orbital robotics ; Path planning ; Robot kinematics ; Scout ant ; Space technology</subject><ispartof>2008 Fourth International Conference on Natural Computation, 2008, Vol.7, p.444-449</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4668017$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,27904,54898</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4668017$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Qingbao Zhu</creatorcontrib><creatorcontrib>Lingling Wang</creatorcontrib><title>A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation</title><title>2008 Fourth International Conference on Natural Computation</title><addtitle>ICNC</addtitle><description>A new ant algorithm for robot path planning is presented according to the latest achievements of research on actual ants. In this algorithm, m scout ants collaborate with each other to search for an optimal or near-optimal path. Of m scout ants, n ants adopt nearest-neighbor search strategy and the left q=m-n ants adopt random search strategy. A section of optimal path will be found after all ants search L steps. Then m ants regard the end point of as the new starting point and search for L steps to find the next section of optimal path . Repeat this process until one of m ants reaches the goal. In this way, the path is consisted of h sections of path with step length L. Carry out the next generation search after step length L is modified, then repeat the searching course mentioned above. An optimal or near-optimal path will be found through comparison after multi-generation of searching. The simulation experiment results show that an optimal or near-optimal path can be planned even in environment with very complex obstacles, which can meet the requirements of real-time planning or navigation. The effect is quite satisfying.</description><subject>Ant algorithm</subject><subject>Collaboration</subject><subject>Convergence</subject><subject>Cooperation</subject><subject>Mathematics</subject><subject>Meeting planning</subject><subject>Mobile robot</subject><subject>Mobile robots</subject><subject>Navigation</subject><subject>Orbital robotics</subject><subject>Path planning</subject><subject>Robot kinematics</subject><subject>Scout ant</subject><subject>Space technology</subject><issn>2157-9555</issn><isbn>9780769533049</isbn><isbn>0769533043</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotzE9LwzAYgPGADpyzR09e8gVa3yRN3uRYi5uDMYd_ziNt0y3SJaONiN9eRE_P5cdDyC2DgjEw9-t6WxccQBdMywuSGdSAykghoDSXZM6ZxNxIKWfk-pcZKJnmVySbpg8AEAwRwczJsqJb90Wr4RBHn44n2seRvsQmJrqz6Uh3gw3BhwN9sJPraAz0tY2fiVYh0TrGsxtt8jHckFlvh8ll_12Q9-XjW_2Ub55X67ra5J6hTDnHVpTMKTS60dwaoVqGvIOSM2OlVrKTreIgUHbQi7bhyrWdaHiHQikruFiQu7-vd87tz6M_2fF7XyqlgaH4AdPES10</recordid><startdate>200810</startdate><enddate>200810</enddate><creator>Qingbao Zhu</creator><creator>Lingling Wang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200810</creationdate><title>A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation</title><author>Qingbao Zhu ; Lingling Wang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-27c341e6798b82a936c172d04219a5865d5c620375d0f3cb26ecd3b2d7366a323</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Ant algorithm</topic><topic>Collaboration</topic><topic>Convergence</topic><topic>Cooperation</topic><topic>Mathematics</topic><topic>Meeting planning</topic><topic>Mobile robot</topic><topic>Mobile robots</topic><topic>Navigation</topic><topic>Orbital robotics</topic><topic>Path planning</topic><topic>Robot kinematics</topic><topic>Scout ant</topic><topic>Space technology</topic><toplevel>online_resources</toplevel><creatorcontrib>Qingbao Zhu</creatorcontrib><creatorcontrib>Lingling Wang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Qingbao Zhu</au><au>Lingling Wang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation</atitle><btitle>2008 Fourth International Conference on Natural Computation</btitle><stitle>ICNC</stitle><date>2008-10</date><risdate>2008</risdate><volume>7</volume><spage>444</spage><epage>449</epage><pages>444-449</pages><issn>2157-9555</issn><isbn>9780769533049</isbn><isbn>0769533043</isbn><abstract>A new ant algorithm for robot path planning is presented according to the latest achievements of research on actual ants. In this algorithm, m scout ants collaborate with each other to search for an optimal or near-optimal path. Of m scout ants, n ants adopt nearest-neighbor search strategy and the left q=m-n ants adopt random search strategy. A section of optimal path will be found after all ants search L steps. Then m ants regard the end point of as the new starting point and search for L steps to find the next section of optimal path . Repeat this process until one of m ants reaches the goal. In this way, the path is consisted of h sections of path with step length L. Carry out the next generation search after step length L is modified, then repeat the searching course mentioned above. An optimal or near-optimal path will be found through comparison after multi-generation of searching. The simulation experiment results show that an optimal or near-optimal path can be planned even in environment with very complex obstacles, which can meet the requirements of real-time planning or navigation. The effect is quite satisfying.</abstract><pub>IEEE</pub><doi>10.1109/ICNC.2008.185</doi><tpages>6</tpages></addata></record>
fulltext	fulltext_linktorsrc
identifier	ISSN: 2157-9555
ispartof	2008 Fourth International Conference on Natural Computation, 2008, Vol.7, p.444-449
issn	2157-9555
language	eng
recordid	cdi_ieee_primary_4668017
source	IEEE Electronic Library (IEL) Conference Proceedings
subjects	Ant algorithm Collaboration Convergence Cooperation Mathematics Meeting planning Mobile robot Mobile robots Navigation Orbital robotics Path planning Robot kinematics Scout ant Space technology
title	A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T16%3A18%3A22IST&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=A%20New%20Algorithm%20for%20Robot%20Path%20Planning%20Based%20on%20Scout%20Ant%20Cooperation&rft.btitle=2008%20Fourth%20International%20Conference%20on%20Natural%20Computation&rft.au=Qingbao%20Zhu&rft.date=2008-10&rft.volume=7&rft.spage=444&rft.epage=449&rft.pages=444-449&rft.issn=2157-9555&rft.isbn=9780769533049&rft.isbn_list=0769533043&rft_id=info:doi/10.1109/ICNC.2008.185&rft_dat=%3Cieee_6IE%3E4668017%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=4668017&rfr_iscdi=true