{"id":"https://openalex.org/W4391936013","doi":"https://doi.org/10.1109/lra.2024.3367271","title":"Tactile Object Property Recognition Using Geometrical Graph Edge Features and Multi-Thread Graph Convolutional Network","display_name":"Tactile Object Property Recognition Using Geometrical Graph Edge Features and Multi-Thread Graph Convolutional Network","publication_year":2024,"publication_date":"2024-02-19","ids":{"openalex":"https://openalex.org/W4391936013","doi":"https://doi.org/10.1109/lra.2024.3367271"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3367271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3367271","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023646170","display_name":"Shardul Kulkarni","orcid":"https://orcid.org/0000-0002-5442-8788"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shardul Kulkarni","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5442-8788","affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085522265","display_name":"Satoshi Funabashi","orcid":"https://orcid.org/0000-0002-6381-3522"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Funabashi","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-6381-3522","affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035429819","display_name":"Alexander Schmitz","orcid":"https://orcid.org/0000-0002-8962-771X"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Alexander Schmitz","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-8962-771X","affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055922202","display_name":"Tetsuya Ogata","orcid":"https://orcid.org/0000-0001-7015-0379"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Ogata","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-7015-0379","affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080654277","display_name":"Shigeki Sugano","orcid":"https://orcid.org/0000-0002-9331-2446"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigeki Sugano","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9331-2446","affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.7232,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.67329174,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"9","issue":"4","first_page":"3894","last_page":"3901"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/computer-science","display_name":"Computer science","score":0.6184285283088684},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5553914308547974},{"id":"https://openalex.org/keywords/thread","display_name":"Thread (computing)","score":0.4728676974773407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3698843717575073},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34867197275161743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3312847316265106},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07735440135002136}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6184285283088684},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5553914308547974},{"id":"https://openalex.org/C138101251","wikidata":"https://www.wikidata.org/wiki/Q213092","display_name":"Thread (computing)","level":2,"score":0.4728676974773407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3698843717575073},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34867197275161743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3312847316265106},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07735440135002136}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3367271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3367271","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8037145768","display_name":"Creation of Human-Robot Coordination Control based on Observation and Insight","funder_award_id":"19H01130","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1529533208","https://openalex.org/W2080200439","https://openalex.org/W2166527963","https://openalex.org/W2209829030","https://openalex.org/W2216666738","https://openalex.org/W2344872270","https://openalex.org/W2558748708","https://openalex.org/W2607241646","https://openalex.org/W2766856748","https://openalex.org/W2940682483","https://openalex.org/W2950697450","https://openalex.org/W2955383310","https://openalex.org/W2979098108","https://openalex.org/W3100674903","https://openalex.org/W3131225419","https://openalex.org/W3131444756","https://openalex.org/W3148711710","https://openalex.org/W3152893301","https://openalex.org/W3197020589","https://openalex.org/W4206234515","https://openalex.org/W4304142231","https://openalex.org/W4308180768","https://openalex.org/W4387448583","https://openalex.org/W4387935000","https://openalex.org/W6702191537","https://openalex.org/W6720975185","https://openalex.org/W6777311388"],"related_works":["https://openalex.org/W2033778626","https://openalex.org/W2187110187","https://openalex.org/W2026780467","https://openalex.org/W2018697868","https://openalex.org/W2002371119","https://openalex.org/W4390492895","https://openalex.org/W2886225742","https://openalex.org/W4323662771","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Performing":[0],"dexterous":[1,260],"tasks":[2,47],"with":[3,96,172,219],"a":[4,50,79,116,136,143,164,182],"multi":[5,132,258],"fingered":[6,259],"robotic":[7],"hand":[8,92,217],"remains":[9],"challenging.":[10],"Tactile":[11],"sensors":[12,150],"provide":[13],"touch":[14],"states":[15],"and":[16,30,60,94,130,157,178],"object":[17,82,191],"features":[18,104,129,177,245],"for":[19,81,187,257],"multifingered":[20],"tasks,":[21],"yet":[22],"the":[23,36,67,153,215,229,241,252],"variety":[24],"in":[25,69,135,201,228],"shapes,":[26],"sizes,":[27],"textures,":[28],"deformabilities":[29],"masses":[31],"of":[32,54,159,166,190,199,225],"everyday":[33],"objects":[34],"makes":[35],"task":[37],"conditions":[38],"diverse.":[39],"Despite":[40],"these":[41,45,127],"challenges,":[42],"humans":[43,64],"accomplish":[44],"difficult":[46],"by":[48],"producing":[49,163],"sensory":[51],"motor":[52],"representation":[53,62],"their":[55],"body.":[56],"This":[57],"combined":[58],"tactile":[59,108,149,168,176],"proprioceptive":[61,244],"enables":[63],"to":[65,73,125,236],"accommodate":[66],"diversity":[68],"daily":[70],"objects.":[71,196],"Referring":[72],"this":[74,76],"concept,":[75],"paper":[77],"presents":[78],"method":[80,254],"property":[83,192],"recognition":[84,184],"using":[85,142],"Graph":[86],"Convolutional":[87],"Networks":[88],"(GCNs),":[89],"leveraging":[90],"robot":[91,216],"proprioception":[93],"morphology":[95],"spatial":[97],"embeddings":[98],"derived":[99],"from":[100,106,146,194],"geometrical":[101],"graph":[102,202],"edge":[103,128,174,230],"acquired":[105,141],"real":[107],"sensor":[109],"alignments":[110],"on":[111,204,240],"an":[112,160],"Allegro":[113,161],"Hand.":[114],"Additionally,":[115],"Multi":[117],"Thread":[118],"GCN":[119,171,206],"(MT":[120],"GCN)":[121],"architecture":[122],"is":[123],"introduced":[124],"process":[126],"basically":[131],"modal":[133],"data":[134,139,144],"graph.":[137],"Training":[138],"was":[140,207,255],"glove,":[145],"tri":[147],"axial":[148],"distributed":[151],"across":[152],"fingertips,":[154],"finger":[155],"phalanges,":[156],"palm":[158],"Hand,":[162],"total":[165],"1152":[167],"measurements.":[169],"MT":[170,205],"proposed":[173,210,253],"features,":[175],"joint":[179,238],"angles":[180],"achieved":[181],"high":[183],"rate,":[185],"86.08%":[186],"six":[188],"classes":[189],"combinations":[193],"eight":[195],"The":[197,209],"effect":[198],"variation":[200],"adjacency":[203],"examined.":[208],"network":[211],"showed":[212],"clusters":[213],"following":[214],"configuration":[218],"t":[220],"SNE":[221],"analysis.":[222],"Furthermore,":[223],"analysis":[224],"learned":[226],"parameters":[227],"feature":[231],"encoder":[232],"demonstrated":[233],"its":[234],"ability":[235],"discern":[237],"positions":[239],"hand,":[242],"acquiring":[243],"effectively.":[246],"Consequently,":[247],"we":[248],"could":[249],"confirm":[250],"that":[251],"effective":[256],"tasks.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}