Cooperation and Coordination Transportation for Nonholonomic Mobile Manipulators: A Distributed Model Predictive Control Approach

This article addresses the problem of cooperation and coordination transportation for decoupling nonholonomic mobile manipulators (NMMs) in a workspace with obstacles. We propose a distributed model predictive control (MPC) approach for a team of NMMs to transport a target object while satisfying si...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on systems, man, and cybernetics. Systems Ročník 53; číslo 2; s. 848 - 860
Hlavní autoři:	Qin, Dongdong, Wu, Jinhui, Liu, Andong, Zhang, Wen-An, Yu, Li
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.02.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Barriers Closed loops Constraints Cooperation Cooperation and coordination transportation Coordination Cost function Decoupling distributed model predictive control (MPC) End effectors Feedback control Force general projection neural network (GPNN) Manipulator dynamics Manipulators Mathematical models modified virtual structure Neural networks nonholonomic mobile manipulators (NMMs) Nonlinear feedback Optimal control Optimization Parameters Predictive control Synchronism Synchronization Task analysis Torque Tracking control Transportation Transportation problem Workspace
ISSN:	2168-2216, 2168-2232
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	This article addresses the problem of cooperation and coordination transportation for decoupling nonholonomic mobile manipulators (NMMs) in a workspace with obstacles. We propose a distributed model predictive control (MPC) approach for a team of NMMs to transport a target object while satisfying significant constraints and limitations, such as the feasible state and control input constraints, parameter synchronization constraints, and obstacles within the workspace. First, under the framework of the decoupling dynamics, an auxiliary dynamics model for task-space end-effectors and null-space mobile bases is obtained by the nonlinear feedback technique based on the Euler-Lagrange description of the NMMs. Using the modified virtual structure method, the cooperation and coordination transportation problem for NMMs is simplified as two independent synchronization tracking control problems for task-space end-effectors and null-space mobile bases. A distributed constrained optimization problem is established by taking the parameter synchronization and system constraints into the cost function. A general projection neural network (GPNN) approach is employed to solve the optimization problem and obtain the optimal control input. Moreover, a sufficient condition that guarantees the stability of the closed-loop system is further developed. Simulation results show that the proposed cooperation and coordination transportation strategy is feasible and effective.
AbstractList	This article addresses the problem of cooperation and coordination transportation for decoupling nonholonomic mobile manipulators (NMMs) in a workspace with obstacles. We propose a distributed model predictive control (MPC) approach for a team of NMMs to transport a target object while satisfying significant constraints and limitations, such as the feasible state and control input constraints, parameter synchronization constraints, and obstacles within the workspace. First, under the framework of the decoupling dynamics, an auxiliary dynamics model for task-space end-effectors and null-space mobile bases is obtained by the nonlinear feedback technique based on the Euler–Lagrange description of the NMMs. Using the modified virtual structure method, the cooperation and coordination transportation problem for NMMs is simplified as two independent synchronization tracking control problems for task-space end-effectors and null-space mobile bases. A distributed constrained optimization problem is established by taking the parameter synchronization and system constraints into the cost function. A general projection neural network (GPNN) approach is employed to solve the optimization problem and obtain the optimal control input. Moreover, a sufficient condition that guarantees the stability of the closed-loop system is further developed. Simulation results show that the proposed cooperation and coordination transportation strategy is feasible and effective.
Author	Yu, Li Liu, Andong Qin, Dongdong Wu, Jinhui Zhang, Wen-An
Author_xml	– sequence: 1 givenname: Dongdong surname: Qin fullname: Qin, Dongdong organization: College of Information Engineering, Zhejiang Provincial United Key Laboratory of Embedded Systems, Zhejiang University of Technology, Hangzhou, China – sequence: 2 givenname: Jinhui surname: Wu fullname: Wu, Jinhui organization: College of Information Engineering, Zhejiang Provincial United Key Laboratory of Embedded Systems, Zhejiang University of Technology, Hangzhou, China – sequence: 3 givenname: Andong orcidid: 0000-0003-2445-8457 surname: Liu fullname: Liu, Andong email: lad@zjut.edu.cn organization: College of Information Engineering, Zhejiang Provincial United Key Laboratory of Embedded Systems, Zhejiang University of Technology, Hangzhou, China – sequence: 4 givenname: Wen-An orcidid: 0000-0002-4355-2783 surname: Zhang fullname: Zhang, Wen-An organization: College of Information Engineering, Zhejiang Provincial United Key Laboratory of Embedded Systems, Zhejiang University of Technology, Hangzhou, China – sequence: 5 givenname: Li orcidid: 0000-0003-3889-3863 surname: Yu fullname: Yu, Li organization: College of Information Engineering, Zhejiang Provincial United Key Laboratory of Embedded Systems, Zhejiang University of Technology, Hangzhou, China
BookMark	eNp9kEtLAzEUhYNUsNb-AHETcN2ax0wy467UJ7QqWNdDJg-aMk3GJBVc-s-dMqULF67ug3PuuXznYOC80wBcYjTFGJU3q_flfEoQIVOKixIhfgKGBLNiQgglg2OP2RkYx7hBCGFSMIrYEPzMvW91EMl6B4VTsJuDsq5frIJwsfUh9aPxAb54t_aNd35rJVz62jYaLoWz7a4RyYd4C2fwzsYUbL1LWnUSpRv4FrSyMtkv3QW4FHwDZ20bvJDrC3BqRBP1-FBH4OPhfjV_mixeH5_ns8VEkpKmSWmYVrnkqqiZoaZ7PpNIY2FYreo6Z1mZI04IKyniNKsR5YZLoxiuM81NntERuO7vdrGfOx1TtfG74LrIinCWY54RVnQq3Ktk8DEGbao22K0I3xVG1R52tYdd7WFXB9idh__xSNsTS0HY5l_nVe-0WutjUlnQjGJOfwEAoJCp
CODEN	ITSMFE
CitedBy_id	crossref_primary_10_1109_TSMC_2025_3526357 crossref_primary_10_1109_TSMC_2024_3390237 crossref_primary_10_1109_TCNS_2023_3256264 crossref_primary_10_1016_j_conengprac_2024_106002 crossref_primary_10_1109_JSYST_2023_3269015 crossref_primary_10_1109_TII_2024_3441647 crossref_primary_10_1109_TAC_2023_3263757 crossref_primary_10_1109_TNNLS_2024_3478215 crossref_primary_10_1002_rnc_70032 crossref_primary_10_1016_j_isatra_2025_08_035 crossref_primary_10_1109_TCYB_2024_3422996 crossref_primary_10_3390_electronics14091783 crossref_primary_10_1016_j_jfranklin_2025_107581 crossref_primary_10_1109_TSMC_2025_3540403 crossref_primary_10_1109_TCYB_2024_3390947 crossref_primary_10_1109_TFUZZ_2025_3554817 crossref_primary_10_1109_ACCESS_2025_3565550 crossref_primary_10_1016_j_automatica_2023_111230 crossref_primary_10_1109_TIE_2024_3451063 crossref_primary_10_1007_s10846_025_02272_x
Cites_doi	10.3390/robotics10030084 10.1109/TIE.2018.2864707 10.1109/TMECH.2009.2024681 10.1109/TNNLS.2019.2923241 10.1016/j.jfranklin.2020.09.025 10.1016/j.conengprac.2019.04.005 10.1109/TIE.2019.2962424 10.1109/TRO.2020.2971416 10.1109/TAC.2016.2612822 10.1109/robot.1993.292110 10.1109/tnnls.2022.3171595 10.1109/JOE.2020.2989603 10.23919/ecc.1997.7082300 10.1115/1.4043053 10.1016/j.neucom.2008.07.008 10.1016/j.ifacol.2020.12.2135 10.1109/iisr.2018.8535773 10.1016/j.neucom.2008.02.016 10.1109/IJCNN.2003.1223776 10.1109/TIE.2016.2642880 10.1109/med.2017.7984201 10.1016/j.robot.2020.103554 10.1109/TSMC.2018.2855444 10.1109/TCYB.2018.2864784 10.1109/TNN.2007.899753 10.1016/j.mechatronics.2021.102497 10.1016/j.jfranklin.2019.09.045 10.1109/tcyb.2021.3104044 10.1109/ICRA.2019.8793476 10.1016/j.automatica.2010.08.012 10.1007/s11432-018-9588-0 10.1080/02286203.2019.1670034 10.1016/j.robot.2018.02.006 10.1016/S0005-1098(98)80015-0 10.1109/TMECH.2008.2008802 10.1016/j.automatica.2020.108917
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023
DBID	97E RIA RIE AAYXX CITATION 7SC 7SP 7TB 8FD FR3 H8D JQ2 L7M L~C L~D
DOI	10.1109/TSMC.2022.3189007
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998-Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database Engineering Research Database Aerospace Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional
DatabaseTitle	CrossRef Aerospace Database Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional
DatabaseTitleList	Aerospace Database
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	2168-2232
EndPage	860
ExternalDocumentID	10_1109_TSMC_2022_3189007 9834317
Genre	orig-research
GrantInformation_xml	– fundername: Fundamental Research Funds for the Provincial Universities of Zhejiang grantid: RF-A2020004 – fundername: National Natural Science Foundation of China grantid: 61973275 funderid: 10.13039/501100001809 – fundername: Zhejiang Provincial Natural Science Foundation of China grantid: LD21F030002 funderid: 10.13039/501100004731
GroupedDBID	0R~ 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFS ACIWK AGQYO AGSQL AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ EBS EJD HZ~ IFIPE IPLJI JAVBF M43 O9- OCL PQQKQ RIA RIE RNS AAYXX CITATION 7SC 7SP 7TB 8FD FR3 H8D JQ2 L7M L~C L~D
ID	FETCH-LOGICAL-c293t-9f6ed5c7d8b6f3f3064c0e1af6bdbb5649507226930734b037f7cfd61b4e7f543
IEDL.DBID	RIE
ISICitedReferencesCount	20
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000829072200001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2168-2216
IngestDate	Mon Jun 30 04:43:13 EDT 2025 Sat Nov 29 03:45:44 EST 2025 Tue Nov 18 22:10:11 EST 2025 Wed Aug 27 02:14:20 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	2
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c293t-9f6ed5c7d8b6f3f3064c0e1af6bdbb5649507226930734b037f7cfd61b4e7f543
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0003-2445-8457 0000-0002-4355-2783 0000-0003-3889-3863
PQID	2765174268
PQPubID	75739
PageCount	13
ParticipantIDs	crossref_primary_10_1109_TSMC_2022_3189007 ieee_primary_9834317 crossref_citationtrail_10_1109_TSMC_2022_3189007 proquest_journals_2765174268
PublicationCentury	2000
PublicationDate	2023-02-01
PublicationDateYYYYMMDD	2023-02-01
PublicationDate_xml	– month: 02 year: 2023 text: 2023-02-01 day: 01
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE transactions on systems, man, and cybernetics. Systems
PublicationTitleAbbrev	TSMC
PublicationYear	2023
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref35 ref12 ref34 ref15 ref14 ref36 ref31 ref30 ref11 ref33 ref10 ref32 ref2 ref1 ref17 ref16 ref19 ref18 ref24 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref27 ref29 ref8 ref7 ref9 ref4 ref3 ref6 ref5
References_xml	– ident: ref9 doi: 10.3390/robotics10030084 – ident: ref31 doi: 10.1109/TIE.2018.2864707 – ident: ref11 doi: 10.1109/TMECH.2009.2024681 – ident: ref2 doi: 10.1109/TNNLS.2019.2923241 – ident: ref27 doi: 10.1016/j.jfranklin.2020.09.025 – ident: ref15 doi: 10.1016/j.conengprac.2019.04.005 – ident: ref22 doi: 10.1109/TIE.2019.2962424 – ident: ref16 doi: 10.1109/TRO.2020.2971416 – ident: ref24 doi: 10.1109/TAC.2016.2612822 – ident: ref34 doi: 10.1109/robot.1993.292110 – ident: ref7 doi: 10.1109/tnnls.2022.3171595 – ident: ref4 doi: 10.1109/JOE.2020.2989603 – ident: ref36 doi: 10.23919/ecc.1997.7082300 – ident: ref13 doi: 10.1115/1.4043053 – ident: ref28 doi: 10.1016/j.neucom.2008.07.008 – ident: ref12 doi: 10.1016/j.ifacol.2020.12.2135 – ident: ref18 doi: 10.1109/iisr.2018.8535773 – ident: ref30 doi: 10.1016/j.neucom.2008.02.016 – ident: ref29 doi: 10.1109/IJCNN.2003.1223776 – ident: ref20 doi: 10.1109/TIE.2016.2642880 – ident: ref25 doi: 10.1109/med.2017.7984201 – ident: ref6 doi: 10.1016/j.robot.2020.103554 – ident: ref23 doi: 10.1109/TSMC.2018.2855444 – ident: ref1 doi: 10.1109/TCYB.2018.2864784 – ident: ref32 doi: 10.1109/TNN.2007.899753 – ident: ref8 doi: 10.1016/j.mechatronics.2021.102497 – ident: ref5 doi: 10.1016/j.jfranklin.2019.09.045 – ident: ref17 doi: 10.1109/tcyb.2021.3104044 – ident: ref26 doi: 10.1109/ICRA.2019.8793476 – ident: ref14 doi: 10.1016/j.automatica.2010.08.012 – ident: ref19 doi: 10.1007/s11432-018-9588-0 – ident: ref10 doi: 10.1080/02286203.2019.1670034 – ident: ref3 doi: 10.1016/j.robot.2018.02.006 – ident: ref35 doi: 10.1016/S0005-1098(98)80015-0 – ident: ref33 doi: 10.1109/TMECH.2008.2008802 – ident: ref21 doi: 10.1016/j.automatica.2020.108917
SSID	ssj0001286306
Score	2.3612213
Snippet	This article addresses the problem of cooperation and coordination transportation for decoupling nonholonomic mobile manipulators (NMMs) in a workspace with...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	848
SubjectTerms	Barriers Closed loops Constraints Cooperation Cooperation and coordination transportation Coordination Cost function Decoupling distributed model predictive control (MPC) End effectors Feedback control Force general projection neural network (GPNN) Manipulator dynamics Manipulators Mathematical models modified virtual structure Neural networks nonholonomic mobile manipulators (NMMs) Nonlinear feedback Optimal control Optimization Parameters Predictive control Synchronism Synchronization Task analysis Torque Tracking control Transportation Transportation problem Workspace
Title	Cooperation and Coordination Transportation for Nonholonomic Mobile Manipulators: A Distributed Model Predictive Control Approach
URI	https://ieeexplore.ieee.org/document/9834317 https://www.proquest.com/docview/2765174268
Volume	53
WOSCitedRecordID	wos000829072200001&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: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 2168-2232 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001286306 issn: 2168-2216 databaseCode: RIE dateStart: 20130101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3LSgMxFL2ouNCFb7FaJQtX4ug8Mnm4K1VxYUtBBXfD5AWFMiNtde-fm5sZS0ER3AwTSGDgZO7JzU3OATiPhUqYYibyfGAimmJ9N9ciosp6OtXOM1RwLXnkw6F4fZWjFbhc3IWx1obDZ_YKX0Mt39T6HbfKrqXIkO9WYZVz1tzVWtpPESwLVpppwjz4_tkWMZNYXj8_Dfo-GUxTn6MKGaN57BINBV-VH8E4MMz99v--bQe22pUk6TXQ78KKrfZgc0lfcB8--3X9ZhuMSVkZ4tt-QjQbgGSha940_eqVDOsKo2G4qkwGtfIhgwzKahxMvurp7Ib0yC1K7aJLljUEndQmZDTFag_GTdJvTr6TXitVfgAv93fP_Yeo9VyItCf-eSQdsybX3AjFXOYwP9GxTUrHlFEqZz6firlfskmMDVTFGXdcO8MSRS13Oc0OYa2qK3sEpKRKM9Srl5RT6aRyZZ4bJaQz0uWGdiD-hqDQrSA5-mJMipCYxLJA1ApErWhR68DFYshbo8bxV-d9hGnRsUWoA91vnIv2f50VKWco2Z0ycfz7qBPYQKP55rx2F9bm03d7Cuv6Yz6eTc_CVPwCwSbdRQ
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1da9swFL30C7o9tOva0azdpoc9lXqRbVmW-hbSlY4lIdAU8masLwgEuyRp3_fPpyu7IdBS6IuxQALDke_R1ZXOAfhJhYq54ibyfGAilmB9N9MiYsp6OtXOM1RwLRnko5GYTuV4Cy7Xd2GsteHwmf2Fr6GWb2r9iFtlXSlS5Ltt2M0YS2hzW2tjR0XwNJhpJjH38PtnW8aMqexO7oZ9nw4mic9ShaRoH7tBRMFZ5UU4Dhxzc_i-r_sEB-1akvQa8I9gy1af4eOGwuAx_OvX9YNtUCZlZYhv-ynRbAGStbJ50_TrVzKqK4yH4bIyGdbKBw0yLKtZsPmqF8sr0iPXKLaLPlnWEPRSm5PxAus9GDlJvzn7TnqtWPkJ3N_8nvRvo9Z1IdKe-leRdNyaTOdGKO5ShxmKpjYuHVdGqYz7jIrmftEmMTowRdPc5doZHitmc5ex9AvsVHVlT4GUTGmOivWS5Uw6qVyZZUYJ6Yx0mWEdoM8QFLqVJEdnjHkRUhMqC0StQNSKFrUOXKyHPDR6HG91PkaY1h1bhDpw_oxz0f6xyyLJOYp2J1x8fX3UD9i_nQwHxeDP6O8ZfEDb-eb09jnsrBaP9hvs6afVbLn4Hqblf2bL4Iw
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=Cooperation+and+Coordination+Transportation+for+Nonholonomic+Mobile+Manipulators%3A+A+Distributed+Model+Predictive+Control+Approach&rft.jtitle=IEEE+transactions+on+systems%2C+man%2C+and+cybernetics.+Systems&rft.au=Qin%2C+Dongdong&rft.au=Wu%2C+Jinhui&rft.au=Liu%2C+Andong&rft.au=Zhang%2C+Wen-An&rft.date=2023-02-01&rft.pub=IEEE&rft.issn=2168-2216&rft.volume=53&rft.issue=2&rft.spage=848&rft.epage=860&rft_id=info:doi/10.1109%2FTSMC.2022.3189007&rft.externalDocID=9834317
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2168-2216&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2168-2216&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2168-2216&client=summon