Enhancing Rover Teleoperation on the Moon With Proprioceptive Sensors and Machine Learning Techniques

Geological formations, environmental conditions, and soil mechanics frequently generate undesired effects on rovers' mobility, such as slippage or sinkage. Underestimating these undesired effects may compromise the rovers' operation and lead to a premature end of the mission. Minimizing mo...

Full description

Saved in:
Bibliographic Details
Published in:IEEE robotics and automation letters Vol. 7; no. 4; pp. 11434 - 11441
Main Authors: Coloma, Sofia, Martinez, Carol, Yalcn, Bars Can, Olivares-Mendez, Miguel A.
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Decision making
Graphical user interface
Graphical user interfaces
Lunar communication
Machine learning
Machine learning for robot control
Mars
Moon
Sensors
Soil
Soil conditions
Soil mechanics
space robotics and automation
telerobotics and teleoperation
Wheels
ISSN:2377-3766, 2377-3766
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract Geological formations, environmental conditions, and soil mechanics frequently generate undesired effects on rovers' mobility, such as slippage or sinkage. Underestimating these undesired effects may compromise the rovers' operation and lead to a premature end of the mission. Minimizing mobility risks becomes a priority for colonising the Moon and Mars. However, addressing this challenge cannot be treated equally for every celestial body since the control strategies may differ; e.g. the low latency Earth-Moon communication allows constant monitoring and controls, something not feasible on Mars. This letter proposes a Hazard Information System (HIS) that estimates the rover's mobility risks (e.g. slippage) using proprioceptive sensors and Machine Learning (supervised and unsupervised). A Graphical User Interface was created to assist human-teleoperation tasks by presenting mobility risk indicators. The system has been developed and evaluated in the lunar analogue facility (LunaLab) at the University of Luxembourg. A real rover and eight participants were part of the experiments. Results demonstrate the benefits of the HIS in the decision-making processes of the operator's response to overcome hazardous situations.
AbstractList Geological formations, environmental conditions, and soil mechanics frequently generate undesired effects on rovers' mobility, such as slippage or sinkage. Underestimating these undesired effects may compromise the rovers' operation and lead to a premature end of the mission. Minimizing mobility risks becomes a priority for colonising the Moon and Mars. However, addressing this challenge cannot be treated equally for every celestial body since the control strategies may differ; e.g. the low latency Earth-Moon communication allows constant monitoring and controls, something not feasible on Mars. This letter proposes a Hazard Information System (HIS) that estimates the rover's mobility risks (e.g. slippage) using proprioceptive sensors and Machine Learning (supervised and unsupervised). A Graphical User Interface was created to assist human-teleoperation tasks by presenting mobility risk indicators. The system has been developed and evaluated in the lunar analogue facility (LunaLab) at the University of Luxembourg. A real rover and eight participants were part of the experiments. Results demonstrate the benefits of the HIS in the decision-making processes of the operator's response to overcome hazardous situations.
Author Yalcn, Bars Can
Olivares-Mendez, Miguel A.
Martinez, Carol
Coloma, Sofia
Author_xml – sequence: 1
  givenname: Sofia
  orcidid: 0000-0001-7603-191X
  surname: Coloma
  fullname: Coloma, Sofia
  email: sofia.coloma@uni.lu
  organization: Space Robotics (SpaceR) Research Group, Interdisciplinary Research Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Esch-sur-Alzette, Luxembourg
– sequence: 2
  givenname: Carol
  orcidid: 0000-0003-3040-6119
  surname: Martinez
  fullname: Martinez, Carol
  email: carol.martinezluna@uni.lu
  organization: Space Robotics (SpaceR) Research Group, Interdisciplinary Research Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Esch-sur-Alzette, Luxembourg
– sequence: 3
  givenname: Bars Can
  surname: Yalcn
  fullname: Yalcn, Bars Can
  email: bariscan.yalcin@uni.lu
  organization: Space Robotics (SpaceR) Research Group, Interdisciplinary Research Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Esch-sur-Alzette, Luxembourg
– sequence: 4
  givenname: Miguel A.
  orcidid: 0000-0001-8824-3231
  surname: Olivares-Mendez
  fullname: Olivares-Mendez, Miguel A.
  email: miguel.olivaresmendez@uni.lu
  organization: Space Robotics (SpaceR) Research Group, Interdisciplinary Research Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Esch-sur-Alzette, Luxembourg
BookMark eNp9kM1LAzEQxYNUsNbeBS8Bz1vz0U02x1LqB7QoteJxSbOzbkpN1uy24H9v1hYRD8LAzOG9ebzfOeo57wChS0pGlBJ1M19ORowwNuJUZVKNT1CfcSkTLoXo_brP0LBpNoQQmjLJVdpHMHOVdsa6N7z0ewh4BVvwNQTdWu9wnLYCvPDxeLVthZ-Cr4P1BurW7gE_g2t8aLB2BV5oU1kHeA46uO7hCkzl7McOmgt0WuptA8PjHqCX29lqep_MH-8eppN5YjjnbaKhUCUdr4Xh41ijzIqxIsYwgFSCSdm60ESnRnBgFFRZxMrCEApE0UxlheIDdH34Wwff5bb5xu-Ci5E5k1GVCpHxqCIHlQm-aQKUeaz0rsNnTkne8cwjz7zjmR95Rov4YzG2_UbUBm23_xmvDkYLAD85KktlKgX_AgazhSk
CODEN IRALC6
CitedBy_id crossref_primary_10_1016_j_autcon_2024_105871
crossref_primary_10_3390_machines13080735
crossref_primary_10_3390_ma15238561
crossref_primary_10_1108_IR_03_2025_0108
crossref_primary_10_3390_biomimetics9110693
crossref_primary_10_1108_IR_11_2022_0289
Cites_doi 10.1016/j.jterra.2021.04.005
10.1109/ICADIWT.2014.6814687
10.20965/jrm.2017.p0902
10.1186/s12864-019-6413-7
10.1016/j.rinp.2019.102617
10.1016/j.jterra.2017.09.001
10.1007/978-3-642-00296-0_5
10.1002/rob.21833
10.1109/AERO.2019.8742084
10.3389/fnbot.2013.00021
10.1017/CBO9781107298019
10.1177/154193120605000909
10.1201/9781315108230
10.2514/6.2021-4137
10.1016/j.actaastro.2018.04.031
10.1613/jair.953
10.1109/ACCESS.2020.3042848
10.1016/j.jterra.2018.12.001
10.1002/rob.21736
10.1109/DSAA49011.2020.00096
10.1504/IJCVR.2020.110641
10.1002/rob.21761
10.1029/2010JE003746
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022
DBID 97E
ESBDL
RIA
RIE
AAYXX
CITATION
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
DOI 10.1109/LRA.2022.3198794
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005–Present
IEEE Xplore Open Access Journals
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE/IET Electronic Library (IEL) (UW System Shared)
CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Technology Research Database
Computer and Information Systems Abstracts – Academic
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
DatabaseTitleList
Technology Research Database
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library (IEL) (UW System Shared)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 2377-3766
EndPage 11441
ExternalDocumentID 10_1109_LRA_2022_3198794
9857576
Genre orig-research
GrantInformation_xml – fundername: 5G-SpaceLab Project
– fundername: Luxembourg National Research Fund
  grantid: 14783405
GroupedDBID 0R~
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACGFS
AGQYO
AGSQL
AHBIQ
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
EBS
EJD
ESBDL
IFIPE
IPLJI
JAVBF
KQ8
M43
M~E
O9-
OCL
RIA
RIE
AAYXX
CITATION
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c333t-aed9f14b6c34879f8d490cc2ee57ec52bda0a5c63e21e9fd2026c01e091898d93
IEDL.DBID RIE
ISICitedReferencesCount 16
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000849259300004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 2377-3766
IngestDate Sun Nov 30 04:32:27 EST 2025
Sat Nov 29 06:03:20 EST 2025
Tue Nov 18 22:12:15 EST 2025
Wed Aug 27 02:14:21 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 4
Language English
License https://creativecommons.org/licenses/by/4.0/legalcode
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c333t-aed9f14b6c34879f8d490cc2ee57ec52bda0a5c63e21e9fd2026c01e091898d93
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0003-3040-6119
0000-0001-8824-3231
0000-0001-7603-191X
OpenAccessLink https://ieeexplore.ieee.org/document/9857576
PQID 2709156683
PQPubID 4437225
PageCount 8
ParticipantIDs proquest_journals_2709156683
crossref_citationtrail_10_1109_LRA_2022_3198794
crossref_primary_10_1109_LRA_2022_3198794
ieee_primary_9857576
PublicationCentury 2000
PublicationDate 2022-10-01
PublicationDateYYYYMMDD 2022-10-01
PublicationDate_xml – month: 10
  year: 2022
  text: 2022-10-01
  day: 01
PublicationDecade 2020
PublicationPlace Piscataway
PublicationPlace_xml – name: Piscataway
PublicationTitle IEEE robotics and automation letters
PublicationTitleAbbrev LRA
PublicationYear 2022
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
ref12
ref11
ref10
ref2
Ludivig (ref15) 2020
ref1
ref17
ref19
ref18
He (ref24) 2005
ref23
ref26
Gmez (ref14) 2011; 8
ref20
ref22
ref21
ref28
ref27
ref8
Bouman (ref25) 1997
ref7
ref9
ref4
ref3
ref6
ref5
Wirth (ref16) 2000
References_xml – ident: ref9
  doi: 10.1016/j.jterra.2021.04.005
– ident: ref26
  doi: 10.1109/ICADIWT.2014.6814687
– ident: ref4
  doi: 10.20965/jrm.2017.p0902
– start-page: 507
  volume-title: Proc. Int. Conf. Neural Inf. Process. Syst.
  year: 2005
  ident: ref24
  article-title: Laplacian score for feature selection
– ident: ref23
  doi: 10.1186/s12864-019-6413-7
– ident: ref3
  doi: 10.1016/j.rinp.2019.102617
– ident: ref2
  doi: 10.1016/j.jterra.2017.09.001
– ident: ref18
  doi: 10.1007/978-3-642-00296-0_5
– ident: ref6
  doi: 10.1002/rob.21833
– ident: ref12
  doi: 10.1109/AERO.2019.8742084
– ident: ref21
  doi: 10.3389/fnbot.2013.00021
– ident: ref17
  doi: 10.1017/CBO9781107298019
– ident: ref28
  doi: 10.1177/154193120605000909
– ident: ref19
  doi: 10.1201/9781315108230
– ident: ref1
  doi: 10.2514/6.2021-4137
– ident: ref8
  doi: 10.1016/j.actaastro.2018.04.031
– year: 1997
  ident: ref25
  article-title: Cluster: An unsupervised algorithm for modeling Gaussian mixtures
– volume: 8
  start-page: 183
  issue: 3
  year: 2011
  ident: ref14
  article-title: Hardware and software architecture for a Rover robot
  publication-title: Revista Avances en Sistemas e Informtica
– start-page: 29
  volume-title: Proc. 4th Int. Conf. Practical Appl. Knowl. Discov. Data Mining
  year: 2000
  ident: ref16
  article-title: CRISP-DM: Towards a standard process model for data mining
– ident: ref20
  doi: 10.1613/jair.953
– ident: ref22
  doi: 10.1109/ACCESS.2020.3042848
– ident: ref10
  doi: 10.1016/j.jterra.2018.12.001
– volume-title: Proc. 71st Int. Astronautical Congr.
  year: 2020
  ident: ref15
  article-title: Building a piece of the Moon: Construction of two indoor lunar analogue environments
– ident: ref11
  doi: 10.1002/rob.21736
– ident: ref27
  doi: 10.1109/DSAA49011.2020.00096
– ident: ref13
  doi: 10.1504/IJCVR.2020.110641
– ident: ref7
  doi: 10.1002/rob.21761
– ident: ref5
  doi: 10.1029/2010JE003746
SSID ssj0001527395
Score 2.316246
Snippet Geological formations, environmental conditions, and soil mechanics frequently generate undesired effects on rovers' mobility, such as slippage or sinkage....
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 11434
SubjectTerms Decision making
Graphical user interface
Graphical user interfaces
Lunar communication
Machine learning
Machine learning for robot control
Mars
Moon
Sensors
Soil
Soil conditions
Soil mechanics
space robotics and automation
telerobotics and teleoperation
Wheels
Title Enhancing Rover Teleoperation on the Moon With Proprioceptive Sensors and Machine Learning Techniques
URI https://ieeexplore.ieee.org/document/9857576
https://www.proquest.com/docview/2709156683
Volume 7
WOSCitedRecordID wos000849259300004&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/IET Electronic Library (IEL) (UW System Shared)
  customDbUrl:
  eissn: 2377-3766
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0001527395
  issn: 2377-3766
  databaseCode: RIE
  dateStart: 20160101
  isFulltext: true
  titleUrlDefault: https://ieeexplore.ieee.org/
  providerName: IEEE
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 2377-3766
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0001527395
  issn: 2377-3766
  databaseCode: M~E
  dateStart: 20160101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFH5sw4Me_DXF6ZQcvAjWdU3bNMchGx6ciE7drbTpqw6kHd3c0b_dl7SbiiIIPeSQlJCvzXtf3sv3AE7JxtPOL2LL8ZWwXE48JXZUankySFRARgWNEtPjtbi5CcZjeVuD89VdGEQ0yWd4oZsmlp_k6k0flXWkLicp_DrUhfDLu1qf5ylaSUx6y0ikLTvXdz3if45DtJSItXS_WR5TSuXH_muMymDrf9PZhs3KeWS9Eu0dqGG2CxtfJAWbgP3sRUtoZM_sTmdnshHZlXyKJdCMHvL42DCnxtNk_sJui3xaTHKT3LJAdk-sNi9mLMoSNjR5lsgqCdZnNlrqvc724GHQH11eWVUpBUtxzudWhIlMu27sK04MRaZB4kpbKQfRE6g8J04iO_KUz5HQkWlC6-Yru4vkTQSEmuT70MjyDA-ABZzbKIRQUqVuEndlbItIh_cUJ1csSFvQWS5zqCqdcV3u4jU0fMOWIQETamDCCpgWnK1GTEuNjT_6NjUQq34VBi1oL5EMq59wFjqCpk_uasAPfx91BOv63WVuXhsa8-INj2FNLeaTWXEC9eF7_8R8ZR_g1tBL
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LS8NAEB58gXrwLdbnHrwIxqbZJJs9FrFUbItofdxCsploQZKS1v5-ZzdpVRRByGEPu2TZL9mZb2f2G4BTsvG084vYcnwlLJcTT4kdlVqeDBIVkFFBo8T02BG9XvD8LG_n4Hx2FwYRTfIZXuimieUnuXrXR2V1qctJCn8eFj3XdezyttbniYrWEpPeNBZpy3rnrkkM0HGImBK1lu4322OKqfzYgY1Zaa3_b0IbsFa5j6xZ4r0Jc5htweoXUcFtwKvsVYtoZC_sTudnsj5ZlnyIJdSMHvL5WDenxtNg_Mpui3xYDHKT3jJBdk-8Ni9GLMoS1jWZlsgqEdYX1p8qvo524KF11b9sW1UxBUtxzsdWhIlMG27sK04cRaZB4kpbKQfRE6g8J04iO_KUz5HwkWlC6-Yru4HkTwSEm-S7sJDlGe4BCzi3UQihpErdJG7I2BaRDvApTs5YkNagPl3mUFVK47rgxVtoGIctQwIm1MCEFTA1OJuNGJYqG3_03dZAzPpVGNTgcIpkWP2Go9ARNH1yWAO-__uoE1hu97udsHPduzmAFf2eMlPvEBbGxTsewZKajAej4th8ax_txtJh
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=Enhancing+Rover+Teleoperation+on+the+Moon+With+Proprioceptive+Sensors+and+Machine+Learning+Techniques&rft.jtitle=IEEE+robotics+and+automation+letters&rft.au=Coloma%2C+Sofia&rft.au=Martinez%2C+Carol&rft.au=Yalcn%2C+Bars+Can&rft.au=Olivares-Mendez%2C+Miguel+A.&rft.date=2022-10-01&rft.pub=IEEE&rft.eissn=2377-3766&rft.volume=7&rft.issue=4&rft.spage=11434&rft.epage=11441&rft_id=info:doi/10.1109%2FLRA.2022.3198794&rft.externalDocID=9857576
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2377-3766&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2377-3766&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2377-3766&client=summon