{"id":"https://openalex.org/W2732791507","doi":"https://doi.org/10.1177/0278364917735594","title":"Grasp Pose Detection in Point Clouds","display_name":"Grasp Pose Detection in Point Clouds","publication_year":2017,"publication_date":"2017-10-30","ids":{"openalex":"https://openalex.org/W2732791507","doi":"https://doi.org/10.1177/0278364917735594","mag":"2732791507"},"language":"en","primary_location":{"id":"doi:10.1177/0278364917735594","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0278364917735594","pdf_url":null,"source":{"id":"https://openalex.org/S73484101","display_name":"The International Journal of Robotics Research","issn_l":"0278-3649","issn":["0278-3649","1741-3176"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The International Journal of Robotics Research","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1706.09911","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053100832","display_name":"Andreas ten Pas","orcid":null},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas ten Pas","raw_affiliation_strings":["Northeastern University, Boston, MA, USA","Northeastern University , Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Northeastern University , Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017321004","display_name":"Marcus Gualtieri","orcid":"https://orcid.org/0000-0002-7806-2186"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marcus Gualtieri","raw_affiliation_strings":["Northeastern University, Boston, MA, USA","Northeastern University , Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Northeastern University , Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075906727","display_name":"Kate Saenko","orcid":"https://orcid.org/0000-0002-7564-7218"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kate Saenko","raw_affiliation_strings":["Boston University, Boston, MA, USA","Boston University; Boston MA, USA"],"affiliations":[{"raw_affiliation_string":"Boston University, Boston, MA, USA","institution_ids":[]},{"raw_affiliation_string":"Boston University; Boston MA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072578581","display_name":"Robert W. Platt","orcid":"https://orcid.org/0000-0002-5981-8443"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Robert Platt","raw_affiliation_strings":["Northeastern University, Boston, MA, USA","Northeastern University , Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Northeastern University , Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072578581"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":3.4656,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.92734597,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"36","issue":"13-14","first_page":"1455","last_page":"1473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10868","display_name":"Soft Robotics and Applications","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.9794811010360718},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.8061832189559937},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7151509523391724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7031739950180054},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6613284349441528},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.655337929725647},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5622349381446838},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4671233296394348},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4647608995437622},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.23124408721923828},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11526888608932495},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.09433558583259583}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9794811010360718},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8061832189559937},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7151509523391724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7031739950180054},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6613284349441528},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.655337929725647},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5622349381446838},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4671233296394348},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4647608995437622},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.23124408721923828},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11526888608932495},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.09433558583259583},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1177/0278364917735594","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0278364917735594","pdf_url":null,"source":{"id":"https://openalex.org/S73484101","display_name":"The International Journal of Robotics Research","issn_l":"0278-3649","issn":["0278-3649","1741-3176"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The International Journal of Robotics Research","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1706.09911","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1706.09911","pdf_url":"https://arxiv.org/pdf/1706.09911","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2732791507","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1706.09911.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1706.09911","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1706.09911","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1706.09911","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1706.09911","pdf_url":"https://arxiv.org/pdf/1706.09911","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1673258135","display_name":null,"funder_award_id":"NNX16AC48A","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G6422938561","display_name":"MANIPULATING SMALL  FLEXIBLE  AND DEFORMABLE OBJECTS IS A KEY CHALLENGE IN DEVELOPING ROBOTS TO WORK WITH HUMANS IN MANUFACTURING AND SPACE APPLICATIONS. IN MANUFACTURING DOMAINS  ASSEMBLY TASKS OFTEN INVOLVE SMALL OR FLEXIBLE MATERIALS SUCH AS CABLES  FABRIC  CARPETING  FLEXIBLE PLASTIC  ETC. IN NASA EXTRA-VEHICULAR REPAIR TASKS  IT IS OFTEN NECESSARY TO MANIPULATE THERMAL BLANKETS IN ORDER TO ACCESS EQUIPMENT. WE PROPOSE USING FORCE AND TACTILE SENSING TO LOCALIZE THESE KINDS OF MATERIALS ACCURATELY DURING IN-HAND MANIPULATION AND THEREBY MAKE DEXTEROUS ROBOT MANIPULATION MORE ROBUST AND PRECISE. PRIOR WORK BY THE PI USING THE NASA-JSC ROBONAUT 2 HAS DEMONSTRATED THAT TACTILE SENSING CAN INDEED BE USED TO MAKE MANIPULATION MORE ROBUST. HOWEVER  IT IS DIFFICULTTO SCALE THE APPROACH UP TO LARGE PROBLEMS BECAUSE OF THE CHALLENGES INVOLVED IN DEVELOPING A HAPTIC MODEL OF WHAT THE MATERIAL IS EXPECTED TO FEEL LIKE. THE PROBLEM IS THAT IT IS HARD TO MODEL FLEXIBLE MATERIALS ANALYTICALLY AND IT CAN BE DIFFICULT TO GATHER A SUFFICIENTLY LARGE AMOUNT OF TRAINING EXPERIENCE TO TRAIN AN ACCURATE MODEL. MOREOVER  EVEN VERY SOPHISTICATED TACTILE SENSORS SOMETIMES PRODUCE VERY NOISY AND ATTENUATED DATA.THIS PROPOSAL IS TO MAKE FLEXIBLE MATERIALS MANIPULATION MORE PRACTICAL BY DEVELOPING NEW METHODS OF CREATING AND USING HAPTIC MODELS. WE PROPOSE TO LEVERAGE EXISTING ROBOT LOCALIZATION AND MAPPING WORK DEVELOPED IN THE MOBILE ROBOT COMMUNITY. ALREADY IN OUR LAB  WE HAVE STARTED THIS WORK AND DEVELOPED AND DEMONSTRATED SOME BASIC TACTILE MAPPING TECHNIQUES THAT WERE SUMMARIZED AT THE 2013 NASA NRI PI MEETING. HERE  WE PROPOSE TO APPLY THIS WORK IN REAL ROBOT MANIPULATION CONTEXTS  CULMINATING IN A DEMONSTRATION OF TACTILE MAPPING AND LOCALIZATION CAPABILITIES IN THE CONTEXT OF SMALL AND FLEXIBLE MATERIALS MANIPULATION TASKS. IN YEAR 1  WE PROPOSE TO CONTINUE TO EXPLORE TACTILE REGISTRATION AND MAPPING TECHNIQUES AND TO DEMONSTRATE BASIC TACTILELOCALIZATION CAPABILITIES IN THE CONTEXT OF A FINE-MATERIALS INSERTION TASK. WE EXPECT THIS WORK TO BE DEMONSTRATED IN THE CONTEXT OF AN EXPERIMENT WITH THE BAXTER ROBOT  LOCATED AT NORTHEASTERN UNIVERSITY. IN YEAR 2  WE PROPOSE TO EXPAND THESE MANIPULATION CAPABILITIES BY DEVELOPING MORE ROBUST AND SOPHISTICATED PLANNING AND CONTROL METHODS THAT REASON ABOUT HOW THE MANIPULATION STRATEGY AFFECTS THE INFORMATION CONTENT AND SAFETY ENVELOPE OF THE MANIPULATION TASK.","funder_award_id":"NNX13AQ85G","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G6779932216","display_name":"NRI: Collaborative Research: Human-Supervised Perception and Grasping in  Clutter","funder_award_id":"1427081","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2732791507.pdf","grobid_xml":"https://content.openalex.org/works/W2732791507.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W46565623","https://openalex.org/W600399566","https://openalex.org/W1503925285","https://openalex.org/W1625949922","https://openalex.org/W1644641054","https://openalex.org/W1892339738","https://openalex.org/W1966747088","https://openalex.org/W1978131245","https://openalex.org/W1999156278","https://openalex.org/W2005756025","https://openalex.org/W2014014888","https://openalex.org/W2021683594","https://openalex.org/W2041376653","https://openalex.org/W2054329862","https://openalex.org/W2076398395","https://openalex.org/W2085949256","https://openalex.org/W2088049833","https://openalex.org/W2090855657","https://openalex.org/W2102605133","https://openalex.org/W2104273718","https://openalex.org/W2109163007","https://openalex.org/W2112796928","https://openalex.org/W2145221543","https://openalex.org/W2155893237","https://openalex.org/W2165308133","https://openalex.org/W2201912979","https://openalex.org/W2290564286","https://openalex.org/W2736534894","https://openalex.org/W2950094539","https://openalex.org/W2951286760","https://openalex.org/W2963654160","https://openalex.org/W3217246742"],"related_works":["https://openalex.org/W2910688493","https://openalex.org/W2963654160","https://openalex.org/W3160245612","https://openalex.org/W3091410168","https://openalex.org/W2949379496","https://openalex.org/W2890031261","https://openalex.org/W3168829710","https://openalex.org/W3146859979","https://openalex.org/W2920104424","https://openalex.org/W3204468004","https://openalex.org/W3203931644","https://openalex.org/W3119129610","https://openalex.org/W2950722529","https://openalex.org/W2902263696","https://openalex.org/W2770715423","https://openalex.org/W3098251352","https://openalex.org/W2946147352","https://openalex.org/W2738786772","https://openalex.org/W2565814686","https://openalex.org/W3090445473"],"abstract_inverted_index":{"Recently,":[0],"a":[1,47,68,109,164,202,209],"number":[2,114,165],"of":[3,63,72,111,115,158,166,186,204],"grasp":[4,17,33,79,99,103,116,175,212],"detection":[5,38,100,176],"methods":[6,43,77,101],"have":[7,86],"been":[8,89],"proposed":[9],"that":[10,149,168,207],"can":[11],"be":[12,92],"used":[13],"to":[14,31,36,81,91,184],"localize":[15],"robotic":[16,197,205],"configurations":[18],"directly":[19],"from":[20],"sensor":[21],"data":[22],"without":[23,66],"estimating":[24],"object":[25,37],"pose.":[26],"The":[27,178],"underlying":[28],"idea":[29],"is":[30,189],"treat":[32],"perception":[34],"analogously":[35],"in":[39,126,129,171,174,181,193,219],"computer":[40],"vision.":[41],"These":[42],"take":[44],"as":[45,59,108],"input":[46],"noisy":[48],"and":[49,57,120],"partially":[50],"occluded":[51],"RGBD":[52],"image":[53],"or":[54,128,195],"point":[55],"cloud":[56],"produce":[58],"output":[60],"pose":[61],"estimates":[62],"viable":[64],"grasps,":[65],"assuming":[67],"known":[69],"CAD":[70],"model":[71],"the":[73,112,145,156],"object.":[74],"Although":[75],"these":[76,135],"generalize":[78],"knowledge":[80],"new":[82],"objects":[83,124,217],"well,":[84],"they":[85],"not":[87,154],"yet":[88],"demonstrated":[90],"reliable":[93],"enough":[94],"for":[95,122,140,215],"wide":[96],"use.":[97],"Many":[98],"achieve":[102],"success":[104,136,213],"rates":[105,137],"(grasp":[106],"successes":[107],"fraction":[110],"total":[113],"attempts)":[117],"between":[118],"75%":[119],"95%":[121],"novel":[123,216],"presented":[125,218],"isolation":[127],"light":[130,146],"clutter.":[131,221],"Not":[132],"only":[133],"are":[134,150],"too":[138],"low":[139],"practical":[141],"grasping":[142],"applications,":[143],"but":[144],"clutter":[147],"scenarios":[148],"evaluated":[151],"often":[152],"do":[153],"reflect":[155],"realities":[157],"real-world":[159],"grasping.":[160],"This":[161],"paper":[162],"proposes":[163],"innovations":[167],"together":[169],"result":[170],"an":[172],"improvement":[173,180],"performance.":[177],"specific":[179],"performance":[182],"due":[183],"each":[185],"our":[187],"contributions":[188],"quantitatively":[190],"measured":[191],"either":[192],"simulation":[194],"on":[196],"hardware.":[198],"Ultimately,":[199],"we":[200],"report":[201],"series":[203],"experiments":[206],"average":[208],"93%":[210],"end-to-end":[211],"rate":[214],"dense":[220]},"counts_by_year":[{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
