Unmanned vehicle path planning using a novel ant colony algorithm

The ant colony optimization algorithm is an effective way to solve the problem of unmanned vehicle path planning. First, establish the environment model of the unmanned vehicle path planning, process and describe the environmental information, and finally realize the division of the problem space. N...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:EURASIP journal on wireless communications and networking Ročník 2019; číslo 1; s. 1 - 9
Hlavní autoři: Yue, Longwang, Chen, Hanning
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 28.05.2019
Springer Nature B.V
SpringerOpen
Témata:
Algorithms
Ant colony algorithm
Ant colony optimization
Biomimetics
Communications Engineering
Distributed Big Data Processing in SCADA Communication Networks
Engineering
Environment models
Grid method
Information Systems Applications (incl.Internet)
Networks
Path planning
Penalty strategy
Product design
Signal,Image and Speech Processing
Unmanned vehicles
Volatility
Path planning
Penalty strategy
Grid method
Ant colony algorithm
ISSN:1687-1499, 1687-1472, 1687-1499
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract The ant colony optimization algorithm is an effective way to solve the problem of unmanned vehicle path planning. First, establish the environment model of the unmanned vehicle path planning, process and describe the environmental information, and finally realize the division of the problem space. Next, the biomimetic behavior of the ant colony algorithm is described. The ant colony algorithm has been improved by adding a penalty strategy. This penalty strategy can enhance the utilization of resources and guide the ants to explore other unknown areas by using the worse value in the search history to enhance the volatility of the pheromone.
AbstractList The ant colony optimization algorithm is an effective way to solve the problem of unmanned vehicle path planning. First, establish the environment model of the unmanned vehicle path planning, process and describe the environmental information, and finally realize the division of the problem space. Next, the biomimetic behavior of the ant colony algorithm is described. The ant colony algorithm has been improved by adding a penalty strategy. This penalty strategy can enhance the utilization of resources and guide the ants to explore other unknown areas by using the worse value in the search history to enhance the volatility of the pheromone.
Abstract The ant colony optimization algorithm is an effective way to solve the problem of unmanned vehicle path planning. First, establish the environment model of the unmanned vehicle path planning, process and describe the environmental information, and finally realize the division of the problem space. Next, the biomimetic behavior of the ant colony algorithm is described. The ant colony algorithm has been improved by adding a penalty strategy. This penalty strategy can enhance the utilization of resources and guide the ants to explore other unknown areas by using the worse value in the search history to enhance the volatility of the pheromone.
ArticleNumber 136
Author Yue, Longwang
Chen, Hanning
Author_xml – sequence: 1
  givenname: Longwang
  surname: Yue
  fullname: Yue, Longwang
  organization: School of Mechanical and Electrical Engineering, Henan University of Technology
– sequence: 2
  givenname: Hanning
  orcidid: 0000-0002-9885-6653
  surname: Chen
  fullname: Chen, Hanning
  email: perfect_chn@hotmail.com
  organization: School of Computer Science and Technology, Tianjin Polytechnic University
BookMark eNp9kEtLxDAUhYMo-PwB7gquq7lJmyZLEV8guNF1uE3TmQ6dZEwygv_e1CqKoJs8bs53ODmHZNd5Zwk5BXoOIMVFBC64LCmoEqqmKusdcgBCNvmm1O6P8z45jHFFKeeVYgfk8tmt0TnbFa92OZjRFhtMy2Iz5uHgFsU2TisWzr_asUCXCuNH794KHBc-DGm5PiZ7PY7RnnzuR-T55vrp6q58eLy9v7p8KE3VyFRakFy1jHGsLVXAQLSSVX2jQEFNwVC0HbW2zc-SI-VoWNe1bY-IvTSm4UfkfvbtPK70JgxrDG_a46A_Bj4sNIY0fUE3HHvGmECBXdV3ohV9UzNulaRCSJi8zmavTfAvWxuTXvltcDm-zgmBSSUZZFUzq0zwMQbbazMkTIN3KeAwaqB66l7P3evcvZ6613Um4Rf5lfc_hs1MzFq3sOE709_QO6tXl9w
CitedBy_id crossref_primary_10_1109_ACCESS_2020_3020629
crossref_primary_10_1007_s11370_020_00313_y
crossref_primary_10_1109_ACCESS_2020_2982040
crossref_primary_10_1177_15501329221123933
crossref_primary_10_1108_IR_10_2020_0218
crossref_primary_10_1177_0954406220963148
crossref_primary_10_1007_s12065_020_00456_y
crossref_primary_10_1109_TVT_2021_3097203
crossref_primary_10_1088_1361_6501_ae02af
crossref_primary_10_1038_s41598_024_52750_9
crossref_primary_10_1016_j_compag_2025_110207
crossref_primary_10_3390_ijerph18136863
crossref_primary_10_1007_s11265_023_01838_y
crossref_primary_10_1007_s11760_023_02989_y
crossref_primary_10_1016_j_swevo_2021_100844
crossref_primary_10_1109_ACCESS_2022_3229171
crossref_primary_10_1177_14727978251366518
crossref_primary_10_1016_j_robot_2021_103949
crossref_primary_10_3390_s23156873
crossref_primary_10_1109_JSEN_2025_3557437
crossref_primary_10_1007_s11831_022_09742_7
crossref_primary_10_1088_1742_6596_1631_1_012092
crossref_primary_10_1177_17298806241278170
crossref_primary_10_3233_JIFS_231280
crossref_primary_10_1016_j_cja_2020_08_033
crossref_primary_10_1088_1742_6596_2891_11_112001
crossref_primary_10_3390_machines12120853
crossref_primary_10_1016_j_oceaneng_2023_114464
crossref_primary_10_1038_s41598_021_95518_1
crossref_primary_10_3390_s23063051
crossref_primary_10_1111_itor_13596
crossref_primary_10_3390_app15137023
crossref_primary_10_1007_s11042_020_09245_2
crossref_primary_10_1016_j_compag_2025_110835
crossref_primary_10_1109_TVT_2021_3093318
crossref_primary_10_1016_j_ast_2021_106857
crossref_primary_10_3390_app13042291
crossref_primary_10_1109_ACCESS_2020_2982617
crossref_primary_10_1186_s13638_022_02205_4
crossref_primary_10_3390_drones7020089
crossref_primary_10_1155_2021_4109821
crossref_primary_10_3390_s24154998
crossref_primary_10_1002_tee_23592
crossref_primary_10_3390_math10193420
crossref_primary_10_1109_ACCESS_2025_3531931
crossref_primary_10_1088_1742_6596_2365_1_012051
Cites_doi 10.1016/j.ins.2017.12.047
10.1109/TEVC.2017.2682899
10.1016/j.asoc.2016.05.011
10.1109/SMC.2013.474
10.1007/978-3-319-91086-4_10
10.1017/S0263574714001878
10.1016/j.asoc.2014.12.002
10.1016/j.asoc.2018.07.050
10.1016/j.ins.2014.11.050
ContentType Journal Article
Copyright The Author(s). 2019
EURASIP Journal on Wireless Communications and Networking is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: The Author(s). 2019
– notice: EURASIP Journal on Wireless Communications and Networking is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID C6C
AAYXX
CITATION
3V.
7SC
7SP
7XB
8AL
8FD
8FE
8FG
8FK
ABUWG
AFKRA
ARAPS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
GNUQQ
HCIFZ
JQ2
K7-
L7M
L~C
L~D
M0N
P5Z
P62
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
Q9U
DOA
DOI 10.1186/s13638-019-1474-5
DatabaseName Springer Nature OA Free Journals
CrossRef
ProQuest Central (Corporate)
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
ProQuest Central (purchase pre-March 2016)
Computing Database (Alumni Edition)
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
Advanced Technologies & Computer Science Collection
ProQuest Central Essentials
ProQuest Central
Technology Collection
ProQuest One Community College
ProQuest Central
ProQuest Central Student
SciTech Premium Collection
ProQuest Computer Science Collection
Computer Science Database
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
Computing Database
Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Premium
ProQuest One Academic (New)
Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest Central Basic
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
Computer Science Database
ProQuest Central Student
Technology Collection
Technology Research Database
Computer and Information Systems Abstracts – Academic
ProQuest One Academic Middle East (New)
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest Central Korea
ProQuest Central (New)
Advanced Technologies Database with Aerospace
Advanced Technologies & Aerospace Collection
ProQuest Computing
ProQuest Central Basic
ProQuest Computing (Alumni Edition)
ProQuest One Academic Eastern Edition
Electronics & Communications Abstracts
ProQuest Technology Collection
ProQuest SciTech Collection
Computer and Information Systems Abstracts Professional
Advanced Technologies & Aerospace Database
ProQuest One Academic UKI Edition
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
DatabaseTitleList

Publicly Available Content Database
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Open Access Full Text
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: PIMPY
  name: Publicly Available Content Database
  url: http://search.proquest.com/publiccontent
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1687-1499
EndPage 9
ExternalDocumentID oai_doaj_org_article_73af2226a6ad4fd6b6f7523e98066817
10_1186_s13638_019_1474_5
GrantInformation_xml – fundername: National key Research and Development Program of China
  grantid: 2017YFB1103603; 2017YFB1103003
– fundername: National Natural Science Foundation of China
  grantid: 61602343; 61772365; 41772123; 61802280; 61806143; 61502318
  funderid: http://dx.doi.org/10.13039/501100001809
– fundername: Federal State Budget Scientific Institution Research Institute - Republican Research and Consulting Center of Expertise (RU)
  grantid: 2017KJ093, 2017KJ094
– fundername: National Natural Science Foundation of China (CN)
  grantid: 51607122
– fundername: Tianjin Province Science and Technology Projects
  grantid: 17JCYBJC15100; 17JCQNJC04500
– fundername: Natural Science Foundation of Henan Province
  grantid: 182300410286
  funderid: http://dx.doi.org/10.13039/501100006407
GroupedDBID -A0
.4S
.DC
0R~
29G
2WC
3V.
4.4
40G
5GY
5VS
6OB
8FE
8FG
8R4
8R5
AAFWJ
AAJSJ
AAKKN
AAKPC
ABDBF
ABEEZ
ABFTD
ABUWG
ACACY
ACGFS
ACUHS
ACULB
ADBBV
ADDVE
ADINQ
ADMLS
AENEX
AFGXO
AFKRA
AFPKN
AHBYD
AHYZX
ALMA_UNASSIGNED_HOLDINGS
AMKLP
ARAPS
ARCSS
AZQEC
BCNDV
BENPR
BGLVJ
BPHCQ
C24
C6C
CCPQU
CS3
DU5
DWQXO
E3Z
EAD
EAP
EAS
EBLON
EBS
EDO
EJD
EMK
ESX
GNUQQ
GROUPED_DOAJ
HCIFZ
HZ~
I-F
K6V
K7-
KQ8
M0N
M~E
OK1
P2P
P62
PIMPY
PQQKQ
PROAC
Q2X
RHU
RNS
RSV
SEG
SOJ
TUS
U2A
XSB
AASML
AAYXX
CITATION
OVT
7SC
7SP
7XB
8AL
8FD
8FK
JQ2
L7M
L~C
L~D
PHGZM
PHGZT
PKEHL
PQEST
PQGLB
PQUKI
PRINS
Q9U
ID FETCH-LOGICAL-c478t-e1839b223a5e091216b824f79191501c0aed0eeba5e83a03ac2ddbbfaaaf8cc73
IEDL.DBID C24
ISICitedReferencesCount 53
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000469495600004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1687-1499
1687-1472
IngestDate Fri Oct 03 12:46:08 EDT 2025
Sat Oct 11 05:52:29 EDT 2025
Sat Nov 29 01:43:52 EST 2025
Tue Nov 18 22:42:46 EST 2025
Fri Feb 21 02:35:33 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Keywords Path planning
Penalty strategy
Grid method
Ant colony algorithm
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c478t-e1839b223a5e091216b824f79191501c0aed0eeba5e83a03ac2ddbbfaaaf8cc73
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0002-9885-6653
OpenAccessLink https://link.springer.com/10.1186/s13638-019-1474-5
PQID 2231289821
PQPubID 237293
PageCount 9
ParticipantIDs doaj_primary_oai_doaj_org_article_73af2226a6ad4fd6b6f7523e98066817
proquest_journals_2231289821
crossref_citationtrail_10_1186_s13638_019_1474_5
crossref_primary_10_1186_s13638_019_1474_5
springer_journals_10_1186_s13638_019_1474_5
PublicationCentury 2000
PublicationDate 2019-05-28
PublicationDateYYYYMMDD 2019-05-28
PublicationDate_xml – month: 05
  year: 2019
  text: 2019-05-28
  day: 28
PublicationDecade 2010
PublicationPlace Cham
PublicationPlace_xml – name: Cham
– name: New York
PublicationTitle EURASIP journal on wireless communications and networking
PublicationTitleAbbrev J Wireless Com Network
PublicationYear 2019
Publisher Springer International Publishing
Springer Nature B.V
SpringerOpen
Publisher_xml – name: Springer International Publishing
– name: Springer Nature B.V
– name: SpringerOpen
References S.P. Carabaza, E. Besada-Portas, J.A. Lopez-Orozco, et al, Ant colony optimization for Multi-UAV minimum time search in uncertain domains[J]. Appl. Soft Comput. 62, 789-806 (2017).
WuWTianYJinTA label based ant colony algorithm for heterogeneous vehicle routing with mixed backhaulAppl. Soft Comput..20164722423410.1016/j.asoc.2016.05.011
BououdenSChadliMKarimiHRAn ant colony optimization-based fuzzy predictive control approach for nonlinear processesInf. Sci.2015299C143158330250810.1016/j.ins.2014.11.050
CastilloONeyoyHSoriaJA new approach for dynamic fuzzy logic parameter tuning in ant colony optimization and its application in fuzzy control of a mobile robotAppl. Soft Comput.201528C15015910.1016/j.asoc.2014.12.002
ZhengFeifeiZecchinAaron C.NewmanJeffery P.MaierHolger R.DandyGraeme C.An Adaptive Convergence-Trajectory Controlled Ant Colony Optimization Algorithm With Application to Water Distribution System Design ProblemsIEEE Transactions on Evolutionary Computation201721577379110.1109/TEVC.2017.2682899
NingJZhangQZhangCA best-path-updating information-guided ant colony optimization algorithmInf. Sci.2018s 433–434142162375901710.1016/j.ins.2017.12.047
ChengJMiaoZLiBAn improved ACO algorithm for mobile robot path planning2017A
ShorakaeiHVahdaniMImaniBOptimal cooperative path planning of unmanned aerial vehicles by a parallel genetic algorithm[J]Robotica2016340482383610.1017/S0263574714001878
FanYWZhangCMHybrid differential evolution algorithm for path planning of mobile robotsJ Taiyuan Univer Sci Technol20194001612
ChengJMiaoZLiBAn improved ACO algorithm for mobile robot path planning2016963968
HsuCCHouRYWangWYPath Planning for Mobile Robots Based on Improved Ant Colony Optimization[C]201310.1109/SMC.2013.474A
L. Wang, R.H. Shi, Application of particle swam optimization algorithm to path planning of unmanned aerial vehicle[J]. Comput. Simul. 28(4), 74-77 (2011).
DorigoMStützleTAnt colony optimization: overview and recent advancesHandbook of Metaheuristics2019ChamSpringer31135110.1007/978-3-319-91086-4_10
ZhangQXiongSRouting optimization of emergency grain distribution vehicles using the immune ant colony optimization algorithmAppl. Soft Comput..20187191792510.1016/j.asoc.2018.07.050
H. Qu, L.W. Huang, X. Ke, Research of improved ant colony based robot path planning under dynamic environment[J]. Dianzi Keji Daxue Xuebao/J. Univ. Electron. Sci. Technol. China, 44(2), 260-265 (2015).
BaoqingGShuyunHLiqiangZMulti-AGV parking path planning based on improved ant colony algorithmJ. Transp. Syst. Eng. Eng.20181865562, 80
M Dorigo (1474_CR5) 2019
G Baoqing (1474_CR9) 2018; 18
J Ning (1474_CR12) 2018; s 433–434
1474_CR3
O Castillo (1474_CR16) 2015; 28
YW Fan (1474_CR4) 2019; 40
1474_CR8
1474_CR11
W Wu (1474_CR14) 2016; 47
J Cheng (1474_CR10) 2016
J Cheng (1474_CR7) 2017
CC Hsu (1474_CR1) 2013
H Shorakaei (1474_CR2) 2016; 34
Feifei Zheng (1474_CR6) 2017; 21
S Bououden (1474_CR13) 2015; 299
Q Zhang (1474_CR15) 2018; 71
References_xml – reference: HsuCCHouRYWangWYPath Planning for Mobile Robots Based on Improved Ant Colony Optimization[C]201310.1109/SMC.2013.474A
– reference: BououdenSChadliMKarimiHRAn ant colony optimization-based fuzzy predictive control approach for nonlinear processesInf. Sci.2015299C143158330250810.1016/j.ins.2014.11.050
– reference: FanYWZhangCMHybrid differential evolution algorithm for path planning of mobile robotsJ Taiyuan Univer Sci Technol20194001612
– reference: ShorakaeiHVahdaniMImaniBOptimal cooperative path planning of unmanned aerial vehicles by a parallel genetic algorithm[J]Robotica2016340482383610.1017/S0263574714001878
– reference: ZhengFeifeiZecchinAaron C.NewmanJeffery P.MaierHolger R.DandyGraeme C.An Adaptive Convergence-Trajectory Controlled Ant Colony Optimization Algorithm With Application to Water Distribution System Design ProblemsIEEE Transactions on Evolutionary Computation201721577379110.1109/TEVC.2017.2682899
– reference: S.P. Carabaza, E. Besada-Portas, J.A. Lopez-Orozco, et al, Ant colony optimization for Multi-UAV minimum time search in uncertain domains[J]. Appl. Soft Comput. 62, 789-806 (2017).
– reference: L. Wang, R.H. Shi, Application of particle swam optimization algorithm to path planning of unmanned aerial vehicle[J]. Comput. Simul. 28(4), 74-77 (2011).
– reference: ZhangQXiongSRouting optimization of emergency grain distribution vehicles using the immune ant colony optimization algorithmAppl. Soft Comput..20187191792510.1016/j.asoc.2018.07.050
– reference: BaoqingGShuyunHLiqiangZMulti-AGV parking path planning based on improved ant colony algorithmJ. Transp. Syst. Eng. Eng.20181865562, 80
– reference: DorigoMStützleTAnt colony optimization: overview and recent advancesHandbook of Metaheuristics2019ChamSpringer31135110.1007/978-3-319-91086-4_10
– reference: WuWTianYJinTA label based ant colony algorithm for heterogeneous vehicle routing with mixed backhaulAppl. Soft Comput..20164722423410.1016/j.asoc.2016.05.011
– reference: ChengJMiaoZLiBAn improved ACO algorithm for mobile robot path planning2016963968
– reference: H. Qu, L.W. Huang, X. Ke, Research of improved ant colony based robot path planning under dynamic environment[J]. Dianzi Keji Daxue Xuebao/J. Univ. Electron. Sci. Technol. China, 44(2), 260-265 (2015).
– reference: ChengJMiaoZLiBAn improved ACO algorithm for mobile robot path planning2017A
– reference: NingJZhangQZhangCA best-path-updating information-guided ant colony optimization algorithmInf. Sci.2018s 433–434142162375901710.1016/j.ins.2017.12.047
– reference: CastilloONeyoyHSoriaJA new approach for dynamic fuzzy logic parameter tuning in ant colony optimization and its application in fuzzy control of a mobile robotAppl. Soft Comput.201528C15015910.1016/j.asoc.2014.12.002
– start-page: 963
  volume-title: An improved ACO algorithm for mobile robot path planning
  year: 2016
  ident: 1474_CR10
– ident: 1474_CR3
– ident: 1474_CR11
– volume: s 433–434
  start-page: 142
  year: 2018
  ident: 1474_CR12
  publication-title: Inf. Sci.
  doi: 10.1016/j.ins.2017.12.047
– volume: 21
  start-page: 773
  issue: 5
  year: 2017
  ident: 1474_CR6
  publication-title: IEEE Transactions on Evolutionary Computation
  doi: 10.1109/TEVC.2017.2682899
– volume: 47
  start-page: 224
  year: 2016
  ident: 1474_CR14
  publication-title: Appl. Soft Comput..
  doi: 10.1016/j.asoc.2016.05.011
– ident: 1474_CR8
– volume-title: An improved ACO algorithm for mobile robot path planning
  year: 2017
  ident: 1474_CR7
– volume: 40
  start-page: 6
  issue: 01
  year: 2019
  ident: 1474_CR4
  publication-title: J Taiyuan Univer Sci Technol
– volume-title: Path Planning for Mobile Robots Based on Improved Ant Colony Optimization[C]
  year: 2013
  ident: 1474_CR1
  doi: 10.1109/SMC.2013.474
– start-page: 311
  volume-title: Handbook of Metaheuristics
  year: 2019
  ident: 1474_CR5
  doi: 10.1007/978-3-319-91086-4_10
– volume: 34
  start-page: 823
  issue: 04
  year: 2016
  ident: 1474_CR2
  publication-title: Robotica
  doi: 10.1017/S0263574714001878
– volume: 28
  start-page: 150
  issue: C
  year: 2015
  ident: 1474_CR16
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2014.12.002
– volume: 71
  start-page: 917
  year: 2018
  ident: 1474_CR15
  publication-title: Appl. Soft Comput..
  doi: 10.1016/j.asoc.2018.07.050
– volume: 18
  start-page: 55
  issue: 6
  year: 2018
  ident: 1474_CR9
  publication-title: J. Transp. Syst. Eng. Eng.
– volume: 299
  start-page: 143
  issue: C
  year: 2015
  ident: 1474_CR13
  publication-title: Inf. Sci.
  doi: 10.1016/j.ins.2014.11.050
SSID ssj0033492
Score 2.4663835
Snippet The ant colony optimization algorithm is an effective way to solve the problem of unmanned vehicle path planning. First, establish the environment model of the...
Abstract The ant colony optimization algorithm is an effective way to solve the problem of unmanned vehicle path planning. First, establish the environment...
SourceID doaj
proquest
crossref
springer
SourceType Open Website
Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 1
SubjectTerms Algorithms
Ant colony algorithm
Ant colony optimization
Biomimetics
Communications Engineering
Distributed Big Data Processing in SCADA Communication Networks
Engineering
Environment models
Grid method
Information Systems Applications (incl.Internet)
Networks
Path planning
Penalty strategy
Product design
Signal,Image and Speech Processing
Unmanned vehicles
Volatility
SummonAdditionalLinks – databaseName: DOAJ Directory of Open Access Journals
  dbid: DOA
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LSwMxEA5SPOhBfGK1Sg6elKXZVx7HKhYPUjxY6S0k2WxbaLelXQv-eyf7qK2gXrwmszB8M8nMMNlvELqBRcGM67ASZbwoCYUntEqhag20YRYy9KJj-vbMej0-GIiXjVFf7k1YSQ9cAtdmoUohhlFFVRKlCdU0ZVA8WcEhWHK_-I-cMFEXU-UdHDrOvaqH6XPaXvoh-BkoIDw_YpEXb0Whgqx_K8P81hQtYk33EB1USSLulModoR2bHaP9DerAE9TpZ1Pl7ki8siMnhd1sYTyvZhBh9559iBXOZis7wQAfdvTU2QdWk-FsMc5H01PU7z6-Pjx51TgEz0SM5551yYyGcK5iC1E-8KnmQZQyASVXTHxDlE2ItRq2eahIqEyQJFqnSqmUG8PCM9TIZpk9R5gmsXEDHuDA0shozY2vTQS1EhEW6kHeRKSGR5qKK9yNrJjIombgVJaISkBUOkRl3ES360_mJVHGb8L3DvO1oOO4LhbA8rKyvPzL8k3Uqi0mq4O3lAAPRFzBA7-J7morfm3_qNHFf2h0ifYC52Pg-gFvoUa-eLdXaNes8vFycV146CfjguZz
  priority: 102
  providerName: Directory of Open Access Journals
– databaseName: Advanced Technologies & Aerospace Database
  dbid: P5Z
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LbxMxEB7R0kN74I0IBOQDp6JV9unHCRVExAFVOZAq4mLZXm-ClGxCso3Ev2dm420IUnPhanvXI894POOxvg_gPTYq4ajCGhsX5WWmImVNhVlrap3wGKG3FdObb-L6Wk4mahQu3DbhWWXnE1tHXS4d3ZEP8BhDV6pkmnxc_YqINYqqq4FC4wQeEkoCUTeMih-dJ84IeY8SLpwvSnKRhqpmIvlgk2RoeSiSop48Kg7OpRa-_yDm_KdM2p4-w8f_K_cTeBTiTna1M5Sn8MDXz-DiLzTC53A1rheG3C7b-hmNYkRXzFaB1ojRE_kpM6xebv2coUYYIV7Xv5mZT3HGZrZ4AePhl--fv0aBYSFyuZBN5Ck-siiiKTwGDmnCrUzzSijM4oo4cbHxZey9xW6ZmTgzLi1LaytjTCWdE9lLOK2XtX8FjJeFI84I9AE8d9ZKl1iXY_oVK48ppuxB3K2vdgF-nFgw5rpNQyTXO5VoVIkmleiiB5d3n6x22BvHBn8ipd0NJNjstmG5nuqwC7XITIUBETfclHlVcssrgZm4VxIjL5mIHvQ7Jeqwlzd6r8EefOjMYN99r0Svj__sDZynZH64T1LZh9NmfevfwpnbNj8363etIf8BTYn2-w
  priority: 102
  providerName: ProQuest
Title Unmanned vehicle path planning using a novel ant colony algorithm
URI https://link.springer.com/article/10.1186/s13638-019-1474-5
https://www.proquest.com/docview/2231289821
https://doaj.org/article/73af2226a6ad4fd6b6f7523e98066817
Volume 2019
WOSCitedRecordID wos000469495600004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Open Access Full Text
  customDbUrl:
  eissn: 1687-1499
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0033492
  issn: 1687-1499
  databaseCode: DOA
  dateStart: 20040101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVAVX
  databaseName: SpringerOpen
  customDbUrl:
  eissn: 1687-1499
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0033492
  issn: 1687-1499
  databaseCode: C24
  dateStart: 20041201
  isFulltext: true
  titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22
  providerName: Springer Nature
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LbxMxEB5BwoEeWp4ibRr5wAm0Yp9-HJMoFRUQrRBFgYtle71ppWQTJWmk_vuOnd1AECDBxQd7vLLGM56ZHfsbgNfYKZhxGdZQmSAtEhEIrUqMWmNtmEUP3WdMv35k4zGfTERev-NeN7fdm5SkP6m9WnP6bh0lKCv4ERFEKUuD7CG0s4gLd49v6J447I7fxMHt1enL3047MEAep__AufwlH-rNzMXJfy3wCRzXXiXp78TgKTyw1TM4-glr8Dn0r6q5cocq2dprR0VcMWKyrIsWEXcBfkoUqRZbOyPIb-LwrKs7ombTxepmcz1_AVcXoy_D90FdPyEwKeObwDrvR6P9V5lFtyCOqOZxWjKBMVoWRiZUtgit1TjMExUmysRFoXWplCq5MSx5Ca1qUdlXQGiRGVcRAjWcpkZrbiJtUgyuQmExgOQdCBumSlODi7saFzPpgwxO5Y47ErkjHXdk1oE3-ynLHbLG34gHbqf2hA4U23csVlNZ65hkiSrR3aGKqiItC6ppyTDOtoKjX8Uj1oFus8-y1tS1RPagiRY8jjrwttnXH8N_XNHpP1GfwePYCQYqRcy70Nqsbu05PDLbzc161YP2YDTOP_e8IPf8bwFsP7AA2zz7juP55af82z0TlvAe
linkProvider Springer Nature
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9QwEB2VggQc-EZdKOADXEBRE9uJ7QNC5aNqtcuKQ4t6M7bjbJG22e3usqh_it_ITDZpKRK99cDVdqw4eX4zk4nnAbzERqMCZVhTFxJZCpMY7yqMWrkPKqKH3mRMvw7UcKgPD82XNfjVnYWh3yo7TmyIupwE-ka-hWYMqdRonr2bniSkGkXZ1U5CYwWLfjz9iSHb_O3eR3y_rzjf-bT_YTdpVQWSIJVeJJF8Ao_TuTyiseRZ4TWXlTIYueRpFlIXyzRGj91auFS4wMvS-8o5V-kQlMB5r8F1KbSifdVXScf8gir9UYCH60syqXibRc10sTXPBCIdH4GhHpnkF-xgIxdwwcf9Ky3bWLudu__bc7oHd1q_mm2vNsJ9WIv1A7j9R7XFh7B9UB87MitsGY9oFCM5ZjZtZZsYHQEYMcfqyTKOGSKOUUXv-pS58QhXuDg6fgQHV7KGx7BeT-q4Aawo80CaGMhxhQze65D5IDG8TE3EEFr3IO3epw1teXVS-RjbJszShV1BwCIELEHA5j14fXbJdFVb5LLB7wkkZwOpLHjTMJmNbMsyVglXocNXuMKVsioLX1Qq5yIajZ6lzlQPNjvQ2Jar5vYcMT1408HuvPufd_Tk8slewM3d_c8DO9gb9p_CLU7QR07gehPWF7Mf8RncCMvF9_nsebOJGHy7ajT-BuvuVcw
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9QwEB2VghAcoHyJhdL6UC5U0SZO4o8DQoV21arVag8UVVxc23G2SNvssrss6l_j1zGTTVqKRG89cI0dK3aeZ-ZlnHkAW3hRS08Z1tj6KCtSHWlnS2St3HkZMEKvM6ZfjmS_r05O9GAFfrX_wtCxytYm1oa6GHv6Rt5FN4amVCuedMvmWMRgt_dh8j0iBSnKtLZyGkuIHIaLn0jfZu8PdvFdv-W8t_f5037UKAxEPpNqHgWKDxwObfOAjpMnwimelVIji8njxMc2FHEIDptVauPUel4UzpXW2lJ5L1Mc9w7clcgx6TjhIP_aeoGUqv4R2cO5RkkmeZNRTZTozpIUUY_Loakli_JrPrGWDrgW7_6Voq09X-_x_7xma_CoibfZznKDPIGVUD2Fh39UYXwGO8fVuSV3wxbhjHoxkmlmk0bOidGvAUNmWTVehBFDJDKq9F1dMDsa4gznZ-fP4fhW5vACVqtxFV4CE0XuSSsDbZ_IvHPKJ85nSDtjHZBaqw7E7bs1vim7TuofI1PTLyXMEg4G4WAIDibvwLvLWybLmiM3df5IgLnsSOXC6wvj6dA01sfI1JYYCAorbJGVhXCilDlPg1YYcapEdmC9BZBpbNjMXKGnA9stBK-a__lEr24ebBPuIwjN0UH_8DU84LQL0FRwtQ6r8-mP8Abu-cX822y6Ue8nBqe3DcbfYI5e8A
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Unmanned+vehicle+path+planning+using+a+novel+ant+colony+algorithm&rft.jtitle=EURASIP+journal+on+wireless+communications+and+networking&rft.au=Yue%2C+Longwang&rft.au=Chen%2C+Hanning&rft.date=2019-05-28&rft.pub=Springer+International+Publishing&rft.eissn=1687-1499&rft.volume=2019&rft.issue=1&rft_id=info:doi/10.1186%2Fs13638-019-1474-5&rft.externalDocID=10_1186_s13638_019_1474_5
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1687-1499&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1687-1499&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1687-1499&client=summon