MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets

Recently, there has been a wealth of development in motion planning for robotic manipulation-new motion planners are continuously proposed, each with their own unique strengths and weaknesses. However, evaluating new planners is challenging and researchers often create their own ad-hoc problems for...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE robotics and automation letters Vol. 7; no. 2; pp. 882 - 889
Main Authors:	Chamzas, Constantinos, Quintero-Pena, Carlos, Kingston, Zachary, Orthey, Andreas, Rakita, Daniel, Gleicher, Michael, Toussaint, Marc, Kavraki, Lydia E.
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Benchmark testing Benchmarks Data sets for robot learning Datasets Feasibility Generators manipulation planning motion and path planning Motion planning Planning Prefabrication Robot sensing systems Robots Task analysis
ISSN:	2377-3766, 2377-3766
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	Recently, there has been a wealth of development in motion planning for robotic manipulation-new motion planners are continuously proposed, each with their own unique strengths and weaknesses. However, evaluating new planners is challenging and researchers often create their own ad-hoc problems for benchmarking, which is time-consuming, prone to bias, and does not directly compare against other state-of-the-art planners. We present MotionBenchMaker , an open-source tool to generate benchmarking datasets for realistic robot manipulation problems. MotionBenchMaker is designed to be an extensible, easy-to-use tool that allows users to both generate datasets and benchmark them by comparing motion planning algorithms. Empirically, we show the benefit of using MotionBenchMaker as a tool to procedurally generate datasets which helps in the fair evaluation of planners. We also present a suite of 40 prefabricated datasets, with 5 different commonly used robots in 8 environments, to serve as a common ground to accelerate motion planning research.
AbstractList	Recently, there has been a wealth of development in motion planning for robotic manipulation—new motion planners are continuously proposed, each with their own unique strengths and weaknesses. However, evaluating new planners is challenging and researchers often create their own ad-hoc problems for benchmarking, which is time-consuming, prone to bias, and does not directly compare against other state-of-the-art planners. We present MotionBenchMaker , an open-source tool to generate benchmarking datasets for realistic robot manipulation problems. MotionBenchMaker is designed to be an extensible, easy-to-use tool that allows users to both generate datasets and benchmark them by comparing motion planning algorithms. Empirically, we show the benefit of using MotionBenchMaker as a tool to procedurally generate datasets which helps in the fair evaluation of planners. We also present a suite of 40 prefabricated datasets, with 5 different commonly used robots in 8 environments, to serve as a common ground to accelerate motion planning research.
Author	Chamzas, Constantinos Kingston, Zachary Orthey, Andreas Gleicher, Michael Toussaint, Marc Rakita, Daniel Quintero-Pena, Carlos Kavraki, Lydia E.
Author_xml	– sequence: 1 givenname: Constantinos orcidid: 0000-0001-5830-5542 surname: Chamzas fullname: Chamzas, Constantinos email: chamzas@rice.edu organization: Department of Computer Science, Rice University, Houston, TX, USA – sequence: 2 givenname: Carlos orcidid: 0000-0003-0915-8691 surname: Quintero-Pena fullname: Quintero-Pena, Carlos email: carlosq@rice.edu organization: Department of Computer Science, Rice University, Houston, TX, USA – sequence: 3 givenname: Zachary orcidid: 0000-0002-3896-5110 surname: Kingston fullname: Kingston, Zachary email: zak@rice.edu organization: Department of Computer Science, Rice University, Houston, TX, USA – sequence: 4 givenname: Andreas orcidid: 0000-0002-1478-1405 surname: Orthey fullname: Orthey, Andreas email: aorthey@is.mpg.de organization: Learning and Intelligent Systems Lab, TU, Berlin, Germany – sequence: 5 givenname: Daniel orcidid: 0000-0001-6292-8515 surname: Rakita fullname: Rakita, Daniel email: rakita@cs.wisc.edu organization: Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA – sequence: 6 givenname: Michael orcidid: 0000-0003-3295-4071 surname: Gleicher fullname: Gleicher, Michael email: gleicher@cs.wisc.edu organization: Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA – sequence: 7 givenname: Marc orcidid: 0000-0002-5487-6767 surname: Toussaint fullname: Toussaint, Marc email: toussaint@tu-berlin.de organization: Learning and Intelligent Systems Lab, TU, Berlin, Germany – sequence: 8 givenname: Lydia E. orcidid: 0000-0003-0699-8038 surname: Kavraki fullname: Kavraki, Lydia E. email: kavraki@rice.edu organization: Department of Computer Science, Rice University, Houston, TX, USA
BookMark	eNp9kM9PwyAYQImZiXPubuKFxHMn8BUo3uavadyiMfPcYEu1W4UJ7OB_b2sXYzx44ju8xwfvEA2sswahY0omlBJ1Nn-aThhhdAIUQBDYQ0MGUiYghRj8mg_QOIQVIYRyJkHxIbpfuFg7e2Fs8bbQa-PP8RQvnWtwdHhmrPE6Gqxtib-Rd-3XuFfwY6Otre0rvtJRBxPDEdqvdBPMeHeO0PPN9fLyNpk_zO4up_OkAC5jQktCGVUcdJmWTGYiFTQridEV1yAKInhaVlyyLFNatxQlIEBVaQoFJy8qgxE67e_dePexNSHmK7f1tl2ZM9EFUKkQLSV6qvAuBG-qvKij7l4eva6bnJK8a5e37fKuXb5r14rkj7jxdfvxz_-Uk16pjTE_uBIpB6ngC_0meKw
CODEN	IRALC6
CitedBy_id	crossref_primary_10_1109_LRA_2022_3191803 crossref_primary_10_1109_LRA_2025_3560885 crossref_primary_10_1016_j_actaastro_2024_12_048 crossref_primary_10_1109_LRA_2024_3469809 crossref_primary_10_1109_LRA_2022_3202633 crossref_primary_10_1108_IR_02_2024_0049 crossref_primary_10_1109_LRA_2025_3544491 crossref_primary_10_1109_LRA_2025_3575307 crossref_primary_10_1109_LRA_2024_3504316 crossref_primary_10_3390_s24092794 crossref_primary_10_1109_ACCESS_2023_3299178 crossref_primary_10_1109_LRA_2023_3286815 crossref_primary_10_1146_annurev_control_061623_094742 crossref_primary_10_1016_j_engappai_2025_111846 crossref_primary_10_1109_LRA_2025_3575013 crossref_primary_10_3390_s25175282 crossref_primary_10_1109_LRA_2023_3296930
Cites_doi	10.1109/LRA.2020.2972837 10.1109/LRA.2020.2964160 10.1109/ICRA48506.2021.9561104 10.1109/IROS45743.2020.9341431 10.1109/ICRA.2015.7139620 10.1109/ICRA48506.2021.9560917 10.1177/0278364911406761 10.1109/ROBOT.1997.619371 10.1109/ICRA40945.2020.9197338 10.1146/annurev-control-091420-084139 10.1109/LRA.2020.2974707 10.3389/frobt.2015.00013 10.1109/ACCESS.2019.2956775 10.1109/IROS47612.2022.9981698 10.1109/MRA.2015.2448951 10.1609/socs.v10i1.18510 10.1109/ICRA.2017.7989545 10.1201/9781439864135-43 10.1109/LRA.2021.3063063 10.1146/annurev-control-060117-104848 10.1109/LRA.2021.3068913 10.1177/02783649231209337 10.1109/IROS45743.2020.9341677 10.1109/ICRA.2018.8460730 10.1109/MRA.2012.2205651 10.1177/0278364917695640 10.1109/LRA.2020.2972870 10.1109/IROS51168.2021.9636651 10.1109/SSRR50563.2020.9292572 10.1007/s10514-012-9321-0 10.1146/annurev-control-060117-105226 10.1109/CVPR42600.2020.01146 10.1109/IVS.2017.7995802 10.1109/LRA.2021.3129136 10.1109/CVPR.2009.5206848 10.1109/TRO.2021.3070975 10.1109/ROBOT.2004.1308891 10.1109/LRA.2020.2965891 10.1109/LRA.2020.2969912 10.1109/MRA.2015.2448276 10.1109/ICRA48506.2021.9562038 10.1109/CRV52889.2021.00019 10.1109/ICRA.2015.7140073 10.1109/ICRA.2016.7487514
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 RIA RIE AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D
DOI	10.1109/LRA.2021.3133603
DatabaseName	IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) 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 Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	2377-3766
EndPage	889
ExternalDocumentID	10_1109_LRA_2021_3133603 9645379
Genre	orig-research
GrantInformation_xml	– fundername: Rice University grantid: NSF 1718478; NSF 2008720; NSF-GRFP 1842494 funderid: 10.13039/100007863 – fundername: NSF grantid: 1830242 – fundername: Deutsche Forschungsgemeinschaft; German Research Foundation grantid: EXC 2002/1-390523135 funderid: 10.13039/501100001659
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 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-c357t-1d0121953ad4d27864618d0eaf5a36c0654df572889aa53a103639f443c50b983
IEDL.DBID	RIE
ISICitedReferencesCount	38
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000733943800001&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 Jun 29 12:33:56 EDT 2025 Tue Nov 18 21:44:32 EST 2025 Sat Nov 29 06:03:14 EST 2025 Wed Aug 27 05:06:25 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-c357t-1d0121953ad4d27864618d0eaf5a36c0654df572889aa53a103639f443c50b983
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-1478-1405 0000-0003-0915-8691 0000-0003-3295-4071 0000-0001-5830-5542 0000-0003-0699-8038 0000-0001-6292-8515 0000-0002-5487-6767 0000-0002-3896-5110
PQID	2613369466
PQPubID	4437225
PageCount	8
ParticipantIDs	crossref_primary_10_1109_LRA_2021_3133603 ieee_primary_9645379 proquest_journals_2613369466 crossref_citationtrail_10_1109_LRA_2021_3133603
PublicationCentury	2000
PublicationDate	2022-04-01
PublicationDateYYYYMMDD	2022-04-01
PublicationDate_xml	– month: 04 year: 2022 text: 2022-04-01 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	ref15 ref14 Dasari (ref27) 2020 ref52 ref11 ref17 ref16 ref19 ref18 ref51 ref50 ref46 ref48 ref42 ref41 ref44 ref43 ucan (ref53) 2008 Chen (ref10) 2020 Mandlekar (ref24) 2018 ref49 ref8 ref7 ref9 ref4 ref3 ref5 Quintero-Pea (ref45) 2021 ref40 ref35 ref34 ref37 ref36 ref31 ref30 Quigley (ref12) 2009 ref33 ref32 ref2 ref1 ref39 ref38 Chitta (ref13) 2012; 19 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref29 Hsu (ref47) 1998 Canny (ref6) 1988
References_xml	– ident: ref31 doi: 10.1109/LRA.2020.2972837 – ident: ref32 doi: 10.1109/LRA.2020.2964160 – ident: ref8 doi: 10.1109/ICRA48506.2021.9561104 – ident: ref29 doi: 10.1109/IROS45743.2020.9341431 – ident: ref50 doi: 10.1109/ICRA.2015.7139620 – ident: ref44 doi: 10.1109/ICRA48506.2021.9560917 – ident: ref49 doi: 10.1177/0278364911406761 – volume-title: Proc. Int. Conf. Learn. Representation year: 2020 ident: ref10 article-title: Learning to plan in high dimensions via neural exploration-exploitation trees – volume: 19 start-page: 18 issue: 1 year: 2012 ident: ref13 publication-title: MoveIt! – start-page: 1--6 volume-title: Proc. IEEE Int. Conf. Robot. Automat. Workshop Open Source Softw. year: 2009 ident: ref12 article-title: ROS: An open-source robot operating system – ident: ref52 doi: 10.1109/ROBOT.1997.619371 – ident: ref51 doi: 10.1109/ICRA40945.2020.9197338 – ident: ref4 doi: 10.1146/annurev-control-091420-084139 – ident: ref25 doi: 10.1109/LRA.2020.2974707 – ident: ref7 doi: 10.3389/frobt.2015.00013 – ident: ref35 doi: 10.1109/ACCESS.2019.2956775 – ident: ref14 doi: 10.1109/IROS47612.2022.9981698 – ident: ref36 doi: 10.1109/MRA.2015.2448951 – ident: ref17 doi: 10.1609/socs.v10i1.18510 – ident: ref2 doi: 10.1109/ICRA.2017.7989545 – start-page: 879 volume-title: Proc. Conf. Robot. Learn. year: 2018 ident: ref24 article-title: Roboturk: A crowdsourcing platform for robotic skill learning through imitation – start-page: 449 volume-title: Proc. Int. Workshop Algorithmic Foundations Robot year: 2008 ident: ref53 article-title: Kinodynamic motion planning by interior-exterior cell exploration – ident: ref48 doi: 10.1201/9781439864135-43 – ident: ref42 doi: 10.1109/LRA.2021.3063063 – ident: ref1 doi: 10.1146/annurev-control-060117-104848 – ident: ref20 doi: 10.1109/LRA.2021.3068913 – ident: ref46 doi: 10.1177/02783649231209337 – ident: ref18 doi: 10.1109/IROS45743.2020.9341677 – ident: ref9 doi: 10.1109/ICRA.2018.8460730 – ident: ref37 doi: 10.1109/MRA.2012.2205651 – ident: ref16 doi: 10.1177/0278364917695640 – ident: ref30 doi: 10.1109/LRA.2020.2972870 – ident: ref43 doi: 10.1109/IROS51168.2021.9636651 – ident: ref19 doi: 10.1109/SSRR50563.2020.9292572 – ident: ref11 doi: 10.1007/s10514-012-9321-0 – ident: ref3 doi: 10.1146/annurev-control-060117-105226 – ident: ref28 doi: 10.1109/CVPR42600.2020.01146 – ident: ref15 doi: 10.1109/IVS.2017.7995802 – ident: ref26 doi: 10.1109/LRA.2021.3129136 – ident: ref34 doi: 10.1109/CVPR.2009.5206848 – ident: ref5 doi: 10.1109/TRO.2021.3070975 – start-page: 885 volume-title: Proc. Conf. Robot. Learn. year: 2020 ident: ref27 article-title: Robonet: Large-scale multi-robot learning – volume-title: The Complexity of Robot Motion Planning year: 1988 ident: ref6 – ident: ref40 doi: 10.1109/ROBOT.2004.1308891 – ident: ref38 doi: 10.1109/LRA.2020.2965891 – volume-title: Proc. IEEE Int. Conf. Robot. Automat. Workshop Mach. Learn. Motion Plan. year: 2021 ident: ref45 article-title: Motion planning via bayesian learning in the dark – start-page: 141 volume-title: Proc. Int. Workshop Algorithmic Foundations Robot year: 1998 ident: ref47 article-title: On finding narrow passages with probabilistic roadmap planners – ident: ref39 doi: 10.1109/LRA.2020.2969912 – ident: ref22 doi: 10.1109/MRA.2015.2448276 – ident: ref33 doi: 10.1109/ICRA48506.2021.9562038 – ident: ref21 doi: 10.1109/CRV52889.2021.00019 – ident: ref41 doi: 10.1109/ICRA.2015.7140073 – ident: ref23 doi: 10.1109/ICRA.2016.7487514
SSID	ssj0001527395
Score	2.4661996
Snippet	Recently, there has been a wealth of development in motion planning for robotic manipulation-new motion planners are continuously proposed, each with their own... Recently, there has been a wealth of development in motion planning for robotic manipulation—new motion planners are continuously proposed, each with their own...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	882
SubjectTerms	Algorithms Benchmark testing Benchmarks Data sets for robot learning Datasets Feasibility Generators manipulation planning motion and path planning Motion planning Planning Prefabrication Robot sensing systems Robots Task analysis
Title	MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets
URI	https://ieeexplore.ieee.org/document/9645379 https://www.proquest.com/docview/2613369466
Volume	7
WOSCitedRecordID	wos000733943800001&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: 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_DXF6Rw5eBGs6680jbepG4LbEJmwW8mSFGWzla7z6N9ukrZTUARvhb4H5UvyXl-S930AZ7aUKm8SYgnXkZaPuYqDDhOWioShZDanhJlG4SEZj8PplD7U4GLdCyOlNJfP5KV-NGf5IuUrvVXWpYGPPULrUCeEFL1aX_spmkmM4uok0qbd4WNP1X-uo8pSzwsqVawy8xgplR_x1ySVwc7_PmcXtsufR9QrRnsPajLZh61vlIJNuB8ZWZ5rNfmeR2wusyvUQ5M0XaA8RQXHdC4RSwQyJq8sm6PCBVX6ReiW5Sq35csDeBr0Jzd3VimYYHEPk9xyhGZoo9hjwhcuCQM_cEJhSxZj5gVc95GKGBM3DCljysrRp7g09n2PY3tGQ-8QGkmayCNA1GYqFlCVQfFMvZ-FMVfBAfu-AtmJsdOCbgVmxEs2cS1qsYhMVWHTSMEfafijEv4WnK893gomjT9smxrutV2JdAva1XhF5VJbRqoEVD6aJv_4d68T2HR1z4K5btOGRp6t5Cls8Pf8ZZl1oD766HfMXPoEL4PEVQ
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LS8QwEB7WB6gH3-Lqqjl4EazbtE3beFtfrOwDkRW8lWySoqxuZbf6-52k7SoogrdCZ6B8SWY6Seb7AI5drTFvRpGjPKqdgEmMg1QoByNhrIUreSRso3A36vfjx0d-V4PTWS-M1tpePtNn5tGe5atMvputsiYPA-ZHfA4WWBB4tOjW-tpRMVxinFVnkS5vdu9bWAF6FAtT3w8rXawy91gxlR8R2KaVm7X_fdA6rJa_j6RVjPcG1PR4E1a-kQpuQadnhXkucPo99cRIT85Jiwyy7IXkGSlYpnNNxFgRa_IqJiNSuJBKwYhciRyzWz7dhoeb68Fl2yklExzpsyh3qDIcbZz5QgXKi-IwCGmsXC1SJvxQmk5SlbLIi2MuBFpRc47L0yDwJXOHPPZ3YH6cjfUuEO4KjAYccygb4vthnEoMDwg8gkxTRuvQrMBMZMknbmQtXhJbV7g8QfgTA39Swl-Hk5nHW8Gl8YftloF7ZlciXYdGNV5JudimCRaB6GOI8vd-9zqCpfag1026t_3OPix7poPBXr5pwHw-edcHsCg_8ufp5NDOqE_sfsZr
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=MotionBenchMaker+%3A+A+Tool+to+Generate+and+Benchmark+Motion+Planning+Datasets&rft.jtitle=IEEE+robotics+and+automation+letters&rft.au=Chamzas%2C+Constantinos&rft.au=Quintero-Pena%2C+Carlos&rft.au=Kingston%2C+Zachary&rft.au=Orthey%2C+Andreas&rft.date=2022-04-01&rft.pub=The+Institute+of+Electrical+and+Electronics+Engineers%2C+Inc.+%28IEEE%29&rft.eissn=2377-3766&rft.volume=7&rft.issue=2&rft.spage=882&rft_id=info:doi/10.1109%2FLRA.2021.3133603&rft.externalDBID=NO_FULL_TEXT
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