Hierarchical detecting points path planning algorithm for climbing robot in spatial trusses

To solve climbing robot path planning in spatial trusses with detecting points, a hierarchical algorithm is proposed according to the divide-and-conquer strategy. Path planning problem with large-scale detecting points is decomposed into a number of path planning sub-problems with small-scale detect...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2017 International Conference on Robotics and Automation Sciences (ICRAS) s. 25 - 29
Hlavní autoři: Erchong Liao, Changan Liu, Limei Jiang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.08.2017
Témata:
Algorithm design and analysis
ant colony optimization algorithm
Classification algorithms
climbing robot
Climbing robots
Clustering algorithms
density peaks clustering algorithm
Path planning
Runtime
traveling salesman problem
ISBN:1538639947, 9781538639948
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract To solve climbing robot path planning in spatial trusses with detecting points, a hierarchical algorithm is proposed according to the divide-and-conquer strategy. Path planning problem with large-scale detecting points is decomposed into a number of path planning sub-problems with small-scale detecting points by Density Peaks Clustering algorithm(DPC), and then all sub-problems with small-scale detecting points are resolved by Ant Colony Optimization algorithm(ACO). At last, all the paths obtained from each subproblem are merged, and local path is optimized by 2-Opt and 3-Opt algorithms. The hierarchical algorithm is tested on 5 different instances. Experimental results show that the proposed algorithm has the same accuracy and computational complexity can be decreased n squared compared with ACO algorithm. The efficiency has been significantly improved.
AbstractList To solve climbing robot path planning in spatial trusses with detecting points, a hierarchical algorithm is proposed according to the divide-and-conquer strategy. Path planning problem with large-scale detecting points is decomposed into a number of path planning sub-problems with small-scale detecting points by Density Peaks Clustering algorithm(DPC), and then all sub-problems with small-scale detecting points are resolved by Ant Colony Optimization algorithm(ACO). At last, all the paths obtained from each subproblem are merged, and local path is optimized by 2-Opt and 3-Opt algorithms. The hierarchical algorithm is tested on 5 different instances. Experimental results show that the proposed algorithm has the same accuracy and computational complexity can be decreased n squared compared with ACO algorithm. The efficiency has been significantly improved.
Author Limei Jiang
Erchong Liao
Changan Liu
Author_xml – sequence: 1
  surname: Erchong Liao
  fullname: Erchong Liao
  email: ecrobot@ncpeu.edu.cn
  organization: Sch. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
– sequence: 2
  surname: Changan Liu
  fullname: Changan Liu
  email: liuchangan@ncpeu.edu.cn
  organization: Sch. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
– sequence: 3
  surname: Limei Jiang
  fullname: Limei Jiang
  email: qhdllmh@163.com
  organization: Sch. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
BookMark eNpFT81KxDAYjKgHd_UF9JIXaE3S5uc7LkXdhQVB9-ZhSdtkG2iTksSDb-8WF7zMMMMwzKzQjQ_eIPRISUkpgedd87H5LBmhslREUqDkCq0or5SoADi__he1vENfW2eijt3gOj3i3mTTZedPeA7O54RnnQc8j9r7xdTjKUSXhwnbEHE3uqld7BjakLHzOJ3j7lyT43dKJt2jW6vHZB4uvEaH15dDsy3272-7ZrMvHJBc1KwXRva8rdR50gKWCMV6qznIWrQgLVioNQWmuBLKSsEs4cIqCloxW63R01-tM8Yc5-gmHX-Ol-_VL3kXUhQ
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/ICRAS.2017.8071910
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE/IET Electronic Library
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 1538639955
9781538639955
EndPage 29
ExternalDocumentID 8071910
Genre orig-research
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i90t-42d6e7d5b389943899f0682dfa59746b97f9f94a19285868f762f056f819a82f3
IEDL.DBID RIE
ISBN 1538639947
9781538639948
IngestDate Wed Jun 26 19:27:25 EDT 2024
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i90t-42d6e7d5b389943899f0682dfa59746b97f9f94a19285868f762f056f819a82f3
PageCount 5
ParticipantIDs ieee_primary_8071910
PublicationCentury 2000
PublicationDate 2017-Aug.
PublicationDateYYYYMMDD 2017-08-01
PublicationDate_xml – month: 08
  year: 2017
  text: 2017-Aug.
PublicationDecade 2010
PublicationTitle 2017 International Conference on Robotics and Automation Sciences (ICRAS)
PublicationTitleAbbrev ICRAS
PublicationYear 2017
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.6490759
Snippet To solve climbing robot path planning in spatial trusses with detecting points, a hierarchical algorithm is proposed according to the divide-and-conquer...
SourceID ieee
SourceType Publisher
StartPage 25
SubjectTerms Algorithm design and analysis
ant colony optimization algorithm
Classification algorithms
climbing robot
Climbing robots
Clustering algorithms
density peaks clustering algorithm
Path planning
Runtime
traveling salesman problem
Title Hierarchical detecting points path planning algorithm for climbing robot in spatial trusses
URI https://ieeexplore.ieee.org/document/8071910
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PT8MgFCZz8eBJzWb8HQ4e7da1FB5Hs7jMy7LoDks8LFBAm2ztslb_fnldt8XEizd4JAQegfeA972PkAcAL-cyCZSGOGDOX3eU4YNAc2CQ2CRSA1OTTYjJBOZzOW2Rxz0WxlpbB5_ZHhbrv3xTpF_4VNYHbw8l4qmOhOAHrJbfs2hnmWhSOO3qsAPJhLL_Mnx9esNILtFrevlFp1Jbk9Hp_8ZxRroHWB6d7g3OOWnZvEPexxliiGtKkyU1Fj8FfCtdF1lelRQZh-m6YSaiavlRbLLqc0W9r0rTZbbSKN4UuqholtMS46t9N4jEKG3ZJbPR82w4DhrGhCCTYRWwyHArTKIxaR7SmksXcoiMU3ht4FoKJ51kynt1kAAH509C5z0g590CBZGLL0g7L3J7SahRkssU4liGmmnQKtII4tExM4qlTlyRDuplsd7mxFg0Krn-W3xDTlD128C5W9L2s7B35Dj9rrJyc18v5A8CaJ20
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFA5jCnpSmeJvc_Bot65N05ejDMeGcwzdYeBhJE2iha0da_XvN6-rDsGLt-QFQvJC8l6S972PkFsAJ-ci8qSC0GPWXXek5l1PcWAQmSiQXV2RTcTjMcxmYtIgdz9YGGNMFXxm2lis_vJ1nnzgU1kHnD0UiKfaiRgL_C1ay-1atLQsrpM4fdfhGybji86w93z_grFccbvu5xehSmVP-gf_G8khOd4C8-jkx-QckYbJWuR1kCKKuCI1WVBt8FvAtdJVnmZlQZFzmK5qbiIqF2_5Oi3fl9R5qzRZpEuF4nWu8pKmGS0wwtp1g1iMwhTHZNp_mPYGXs2Z4KXCLz0WaG5iHSlMm4fE5sL6HAJtJV4cuBKxFVYw6fw6iICDdWehdT6QdY6BhMCGJ6SZ5Zk5JVRLwUUCYSh8xRQoGSiE8aiQackSG5-RFuplvtpkxZjXKjn_W3xD9gbTp9F8NBw_XpB9XIZNGN0laboZmSuym3yWabG-rhb1C2dToPs
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%3Abook&rft.genre=proceeding&rft.title=2017+International+Conference+on+Robotics+and+Automation+Sciences+%28ICRAS%29&rft.atitle=Hierarchical+detecting+points+path+planning+algorithm+for+climbing+robot+in+spatial+trusses&rft.au=Erchong+Liao&rft.au=Changan+Liu&rft.au=Limei+Jiang&rft.date=2017-08-01&rft.pub=IEEE&rft.isbn=1538639947&rft.spage=25&rft.epage=29&rft_id=info:doi/10.1109%2FICRAS.2017.8071910&rft.externalDocID=8071910
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781538639948/lc.gif&client=summon&freeimage=true
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781538639948/mc.gif&client=summon&freeimage=true
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781538639948/sc.gif&client=summon&freeimage=true