Generation of Optimal Coverage Paths for Mobile Robots Using Hybrid Genetic Algorithm

This paper presents new optimal offline approaches to solve the coverage path planning problem. A novel hybrid genetic algorithm (HGA), which uses, the turn-away starting point and backtracking spiral algorithms for performing local search, is proposed for grid-based environmental representations. T...

Full description

Saved in:
Bibliographic Details
Published in:Journal of robotics and mechatronics Vol. 33; no. 1; pp. 11 - 23
Main Authors: Schäfle, Tobias Rainer, Mitschke, Marcel, Uchiyama, Naoki
Format: Journal Article
Language:English
Published: Tokyo Fuji Technology Press Co. Ltd 20.02.2021
Subjects:
Energy value
Fitness
Genetic algorithms
Path planning
Travel time
ISSN:0915-3942, 1883-8049
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract This paper presents new optimal offline approaches to solve the coverage path planning problem. A novel hybrid genetic algorithm (HGA), which uses, the turn-away starting point and backtracking spiral algorithms for performing local search, is proposed for grid-based environmental representations. The HGA algorithm is validated using the following three different fitness functions: the number of cell visits, traveling time, and a new energy fitness function based on experimentally acquired energy values of fundamental motions. Computational results show that compared to conventional methods, HGA improves paths up to 38.4%; moreover, HGAs have a consistent fitness for different starting positions in an environment. Furthermore, experimental results prove the validity of the fitness function.
AbstractList This paper presents new optimal offline approaches to solve the coverage path planning problem. A novel hybrid genetic algorithm (HGA), which uses, the turn-away starting point and backtracking spiral algorithms for performing local search, is proposed for grid-based environmental representations. The HGA algorithm is validated using the following three different fitness functions: the number of cell visits, traveling time, and a new energy fitness function based on experimentally acquired energy values of fundamental motions. Computational results show that compared to conventional methods, HGA improves paths up to 38.4%; moreover, HGAs have a consistent fitness for different starting positions in an environment. Furthermore, experimental results prove the validity of the fitness function.
Author Uchiyama, Naoki
Mitschke, Marcel
Schäfle, Tobias Rainer
Author_xml – sequence: 1
  givenname: Tobias Rainer
  surname: Schäfle
  fullname: Schäfle, Tobias Rainer
– sequence: 2
  givenname: Marcel
  surname: Mitschke
  fullname: Mitschke, Marcel
– sequence: 3
  givenname: Naoki
  surname: Uchiyama
  fullname: Uchiyama, Naoki
BookMark eNp1kEFrAjEQhUOxUGs99xroeTXZbDabo0irBYul1HPIJlmNrJttEgv--0btqdC5zDDMm5n33YNB5zoDwCNGkxzxkk73_pCqHE96hDC-AUNcVSSrUMEHYIg4phnhRX4HxiHsUQpaME7YEGwWpjNeRus66Bq47qM9yBbO3Xfqbg18l3EXYOM8fHO1bQ38cLWLAW6C7bZweaq91fC8I1oFZ-3WeRt3hwdw28g2mPFvHoHNy_PnfJmt1ovX-WyVqaJEMdPMlKyhNW8qLImmRcMUJRVniFHDKqZLQmStdIHTtzrPdSXLsmY50UpKzBUZgafr3t67r6MJUezd0XfppMgLjhEuk9E0Nb1OKe9C8KYRvU8u_UlgJC74RMInzvjEBV9S0D8KZeMFUvTStv_qfgCzr3Zs
CitedBy_id crossref_primary_10_20965_jrm_2021_p1423
crossref_primary_10_1088_1742_6596_2425_1_012065
crossref_primary_10_1155_2021_9975538
crossref_primary_10_20965_jrm_2024_p1262
crossref_primary_10_20965_jaciii_2023_p0710
crossref_primary_10_1017_S0263574724000377
crossref_primary_10_20965_jaciii_2022_p0315
crossref_primary_10_20965_jrm_2025_p0720
Cites_doi 10.1007/s00778-015-0378-1
10.1109/TRO.2005.861455
10.1016/S0925-7721(02)00110-4
10.1109/TSMCB.2003.811769
10.1016/j.rcim.2016.02.002
10.20965/jrm.2017.p0838
10.1007/0-306-48056-5_5
10.1109/TRO.2017.2780259
10.1016/j.jides.2016.05.004
10.1016/S0925-7721(00)00015-8
10.7551/mitpress/3927.001.0001
10.1177/027836402320556359
10.1007/978-3-642-01970-8_4
10.20965/jrm.2019.p0464
10.20965/jrm.2018.p0005
10.1023/A:1016610507833
10.1109/ICDE.2014.6816646
10.1515/9780691187563
10.1016/j.robot.2011.06.002
10.1109/ELECSYM.2016.7860983
10.1007/978-1-4471-1273-0_32
10.1109/AIM.2007.4412480
10.1109/ICCES.2018.8639412
ContentType Journal Article
Copyright Copyright © 2021 Fuji Technology Press Ltd.
Copyright_xml – notice: Copyright © 2021 Fuji Technology Press Ltd.
CorporateAuthor Andreas Stihl AG & Co. KG Badstraße 115, Waiblingen 71336, Germany
Department of Mechanical Engineering, Toyohashi University of Technology 1-1 Hibarigaoka, Tempaku, Toyohashi, Aichi 441-8580, Japan
CorporateAuthor_xml – name: Andreas Stihl AG & Co. KG Badstraße 115, Waiblingen 71336, Germany
– name: Department of Mechanical Engineering, Toyohashi University of Technology 1-1 Hibarigaoka, Tempaku, Toyohashi, Aichi 441-8580, Japan
DBID AAYXX
CITATION
7SC
7SP
8FD
8FE
8FG
AFKRA
ARAPS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
GNUQQ
HCIFZ
JQ2
K7-
L7M
L~C
L~D
P5Z
P62
PHGZM
PHGZT
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
DOI 10.20965/jrm.2021.p0011
DatabaseName CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Central UK/Ireland
Advanced Technologies & Aerospace Database
ProQuest Central Essentials Local Electronic Collection Information
ProQuest Central
Technology collection
ProQuest One
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
Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Premium
ProQuest One Academic
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
DatabaseTitle CrossRef
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
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 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)
DatabaseTitleList Computer Science Database
CrossRef
Database_xml – sequence: 1
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1883-8049
EndPage 23
ExternalDocumentID 10_20965_jrm_2021_p0011
GroupedDBID 7.U
AAYXX
AFFHD
AFKRA
ALMA_UNASSIGNED_HOLDINGS
ARAPS
BENPR
BGLVJ
CCPQU
CITATION
EBS
EJD
GROUPED_DOAJ
HCIFZ
ISHAI
JSF
JSH
K7-
OK1
P2P
PHGZM
PHGZT
PQGLB
RJT
RZJ
7SC
7SP
8FD
8FE
8FG
AZQEC
DWQXO
GNUQQ
JQ2
L7M
L~C
L~D
P62
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
ID FETCH-LOGICAL-c460t-d7e67f5b9f81a3d54f7c53897075e787d633abcd41479d22d8a66b723dcaa19c3
IEDL.DBID K7-
ISICitedReferencesCount 9
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000621401900002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 0915-3942
IngestDate Sun Nov 30 04:10:20 EST 2025
Sat Nov 29 06:26:31 EST 2025
Tue Nov 18 20:50:48 EST 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c460t-d7e67f5b9f81a3d54f7c53897075e787d633abcd41479d22d8a66b723dcaa19c3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
OpenAccessLink https://doi.org/10.20965/jrm.2021.p0011
PQID 2491016054
PQPubID 4911629
PageCount 13
ParticipantIDs proquest_journals_2491016054
crossref_primary_10_20965_jrm_2021_p0011
crossref_citationtrail_10_20965_jrm_2021_p0011
PublicationCentury 2000
PublicationDate 2021-02-20
PublicationDateYYYYMMDD 2021-02-20
PublicationDate_xml – month: 02
  year: 2021
  text: 2021-02-20
  day: 20
PublicationDecade 2020
PublicationPlace Tokyo
PublicationPlace_xml – name: Tokyo
PublicationTitle Journal of robotics and mechatronics
PublicationYear 2021
Publisher Fuji Technology Press Co. Ltd
Publisher_xml – name: Fuji Technology Press Co. Ltd
References key-10.20965/jrm.2021.p0011-31
key-10.20965/jrm.2021.p0011-9
key-10.20965/jrm.2021.p0011-30
key-10.20965/jrm.2021.p0011-8
key-10.20965/jrm.2021.p0011-11
key-10.20965/jrm.2021.p0011-33
key-10.20965/jrm.2021.p0011-7
key-10.20965/jrm.2021.p0011-10
key-10.20965/jrm.2021.p0011-32
key-10.20965/jrm.2021.p0011-2
key-10.20965/jrm.2021.p0011-1
key-10.20965/jrm.2021.p0011-6
key-10.20965/jrm.2021.p0011-5
key-10.20965/jrm.2021.p0011-4
key-10.20965/jrm.2021.p0011-3
key-10.20965/jrm.2021.p0011-17
key-10.20965/jrm.2021.p0011-39
key-10.20965/jrm.2021.p0011-16
key-10.20965/jrm.2021.p0011-38
key-10.20965/jrm.2021.p0011-19
key-10.20965/jrm.2021.p0011-18
key-10.20965/jrm.2021.p0011-13
key-10.20965/jrm.2021.p0011-35
key-10.20965/jrm.2021.p0011-12
key-10.20965/jrm.2021.p0011-34
key-10.20965/jrm.2021.p0011-15
key-10.20965/jrm.2021.p0011-37
key-10.20965/jrm.2021.p0011-14
key-10.20965/jrm.2021.p0011-36
key-10.20965/jrm.2021.p0011-20
key-10.20965/jrm.2021.p0011-22
key-10.20965/jrm.2021.p0011-21
key-10.20965/jrm.2021.p0011-40
key-10.20965/jrm.2021.p0011-28
key-10.20965/jrm.2021.p0011-27
key-10.20965/jrm.2021.p0011-29
key-10.20965/jrm.2021.p0011-24
key-10.20965/jrm.2021.p0011-23
key-10.20965/jrm.2021.p0011-26
key-10.20965/jrm.2021.p0011-25
References_xml – ident: key-10.20965/jrm.2021.p0011-7
  doi: 10.1007/s00778-015-0378-1
– ident: key-10.20965/jrm.2021.p0011-15
  doi: 10.1109/TRO.2005.861455
– ident: key-10.20965/jrm.2021.p0011-18
  doi: 10.1016/S0925-7721(02)00110-4
– ident: key-10.20965/jrm.2021.p0011-12
– ident: key-10.20965/jrm.2021.p0011-20
  doi: 10.1109/TSMCB.2003.811769
– ident: key-10.20965/jrm.2021.p0011-1
  doi: 10.1016/j.rcim.2016.02.002
– ident: key-10.20965/jrm.2021.p0011-9
  doi: 10.20965/jrm.2017.p0838
– ident: key-10.20965/jrm.2021.p0011-39
– ident: key-10.20965/jrm.2021.p0011-40
  doi: 10.1007/0-306-48056-5_5
– ident: key-10.20965/jrm.2021.p0011-4
– ident: key-10.20965/jrm.2021.p0011-2
– ident: key-10.20965/jrm.2021.p0011-24
  doi: 10.1109/TRO.2017.2780259
– ident: key-10.20965/jrm.2021.p0011-35
– ident: key-10.20965/jrm.2021.p0011-16
– ident: key-10.20965/jrm.2021.p0011-32
  doi: 10.1016/j.jides.2016.05.004
– ident: key-10.20965/jrm.2021.p0011-6
– ident: key-10.20965/jrm.2021.p0011-10
  doi: 10.1016/S0925-7721(00)00015-8
– ident: key-10.20965/jrm.2021.p0011-30
– ident: key-10.20965/jrm.2021.p0011-37
  doi: 10.7551/mitpress/3927.001.0001
– ident: key-10.20965/jrm.2021.p0011-14
  doi: 10.1177/027836402320556359
– ident: key-10.20965/jrm.2021.p0011-22
  doi: 10.1007/978-3-642-01970-8_4
– ident: key-10.20965/jrm.2021.p0011-8
  doi: 10.20965/jrm.2019.p0464
– ident: key-10.20965/jrm.2021.p0011-21
– ident: key-10.20965/jrm.2021.p0011-26
  doi: 10.20965/jrm.2018.p0005
– ident: key-10.20965/jrm.2021.p0011-23
– ident: key-10.20965/jrm.2021.p0011-25
– ident: key-10.20965/jrm.2021.p0011-17
  doi: 10.1023/A:1016610507833
– ident: key-10.20965/jrm.2021.p0011-5
  doi: 10.1109/ICDE.2014.6816646
– ident: key-10.20965/jrm.2021.p0011-38
  doi: 10.1515/9780691187563
– ident: key-10.20965/jrm.2021.p0011-29
  doi: 10.1016/j.robot.2011.06.002
– ident: key-10.20965/jrm.2021.p0011-36
– ident: key-10.20965/jrm.2021.p0011-11
– ident: key-10.20965/jrm.2021.p0011-3
– ident: key-10.20965/jrm.2021.p0011-34
  doi: 10.1109/ELECSYM.2016.7860983
– ident: key-10.20965/jrm.2021.p0011-19
– ident: key-10.20965/jrm.2021.p0011-13
  doi: 10.1007/978-1-4471-1273-0_32
– ident: key-10.20965/jrm.2021.p0011-31
– ident: key-10.20965/jrm.2021.p0011-27
  doi: 10.1109/AIM.2007.4412480
– ident: key-10.20965/jrm.2021.p0011-33
  doi: 10.1109/ICCES.2018.8639412
– ident: key-10.20965/jrm.2021.p0011-28
SSID ssj0000547937
Score 2.2473664
Snippet This paper presents new optimal offline approaches to solve the coverage path planning problem. A novel hybrid genetic algorithm (HGA), which uses, the...
SourceID proquest
crossref
SourceType Aggregation Database
Enrichment Source
Index Database
StartPage 11
SubjectTerms Energy value
Fitness
Genetic algorithms
Path planning
Travel time
Title Generation of Optimal Coverage Paths for Mobile Robots Using Hybrid Genetic Algorithm
URI https://www.proquest.com/docview/2491016054
Volume 33
WOSCitedRecordID wos000621401900002&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 Directory of Open Access Journals
  customDbUrl:
  eissn: 1883-8049
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000547937
  issn: 0915-3942
  databaseCode: DOA
  dateStart: 20070101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVPQU
  databaseName: Advanced Technologies & Aerospace Database
  customDbUrl:
  eissn: 1883-8049
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000547937
  issn: 0915-3942
  databaseCode: P5Z
  dateStart: 20150201
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/hightechjournals
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Computer Science Database
  customDbUrl:
  eissn: 1883-8049
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000547937
  issn: 0915-3942
  databaseCode: K7-
  dateStart: 20150201
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/compscijour
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl:
  eissn: 1883-8049
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000547937
  issn: 0915-3942
  databaseCode: BENPR
  dateStart: 20150201
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV05T8MwFLagMMDAjShH5YGBxdA4TlxPCKoiBigVolLFEsV2zKHSQBOQ-Pe856YcAywsWXzE8md_frafv0fIvpCoMqYc06mWTDgrWaqFYAqW9zhWIg6cF3G9kN1uazBQverArajcKqec6Ina5gbPyI9gm-DV0CJx_PzCMGoU3q5WITRmyVzAgYTxUlayzzMWyIzyb15uL4hYqASfqPtw1Dw5ehzjU3QOXIWG0c-F6Scv-8XmbPm_zVwhS5WZSU8m42KVzGSjNbL4TXxwnfQnitMIDM0dvQLueIIibfTpBJKhPbANCwo2Lb3MNXAHvc51XhbUOxnQ83d86kWxDvgFPRneQSvK-6cN0j_r3LTPWRVkgRkRN0tmZRZLF2nlWkEa2kg4aYAElQRbIoPZbOMwTLWxIoC-tJzbVhrHWvLQmjQNlAk3SW2Uj7ItQhUK1UiXicCA0cC5bgojpbRpxh13xtXJ4bSHE1MpkGMgjGECOxEPSQKQJAhJ4iGpk4PPAs8T8Y3fs-5O8UiqWVgkX2Bs_528QxawKv9UvblLauX4Ndsj8-atfCjGDTJ32un2rht-v97wQwy-vej2A1j11wY
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9QwEB2VLRLlwDeiUMAHkLiYbhzHXh8QKqXVVt0uq6qVeguxHVNQuymbAOqf4jcy4ySFHuDWA-fETpx5eTP-mDcAL6QmlTETuC2s5jJ4zQsrJTfo3pUyUiUhirhO9HQ6OjoysyX42efC0LHKnhMjUfvK0Rr5Ok4TohpaJt-efeVUNYp2V_sSGi0sdsvzHzhlq9_svEf7vhRie-tgc8y7qgLcSTVsuNel0iGzJoySIvWZDNrhX280Os8S4etVmhbWeZlIbbwQflQoZbVIvSuKxLgU-70GyzKVKhvA8rut6Wz_YlUHX48E56LAX5Lx1EjR6gkJUllZ_7Kg5HeB7Eih2GVXeNkTRPe2fft_-zB34FYXSLONFvl3Yamc34Obf8gr3ofDVlOboMeqwD4gO55ik006tYo0ymYY_dYMo3a2V1lkR7Zf2aqpWTxGwcbnlMzGqA98BNs4-YSjbo5PH8DhlYzrIQzm1bx8BMyQFI8OpUwchkVC2KF0WmtflCKI4MIqvO4tmrtOY51KfZzkONeKEMgRAjlBII8QWIVXFw3OWnmRv9-61ts_73imzn8b__G_Lz-HG-ODvUk-2ZnuPoEV6jYm5g_XYNAsvpVP4br73nyuF886SDP4eNVg-QVa3jIS
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=Generation+of+Optimal+Coverage+Paths+for+Mobile+Robots+Using+Hybrid+Genetic+Algorithm&rft.jtitle=Journal+of+robotics+and+mechatronics&rft.au=Sch%C3%A4fle%2C+Tobias+Rainer&rft.au=Mitschke+Marcel&rft.au=Uchiyama+Naoki&rft.date=2021-02-20&rft.pub=Fuji+Technology+Press+Co.+Ltd&rft.issn=0915-3942&rft.eissn=1883-8049&rft.volume=33&rft.issue=1&rft.spage=11&rft.epage=23&rft_id=info:doi/10.20965%2Fjrm.2021.p0011
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0915-3942&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0915-3942&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0915-3942&client=summon