{"id":"https://openalex.org/W7125953428","doi":"https://doi.org/10.1109/smc58881.2025.11342497","title":"MTF-Grasp: A Multi-tier Federated Learning Approach for Robotic Grasping","display_name":"MTF-Grasp: A Multi-tier Federated Learning Approach for Robotic Grasping","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125953428","doi":"https://doi.org/10.1109/smc58881.2025.11342497"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-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/A5048326847","display_name":"Obaidullah Zaland","orcid":"https://orcid.org/0009-0009-8763-4391"},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Obaidullah Zaland","raw_affiliation_strings":["Umeå Unviersity,Department of Computing Science,Umeå,Sweden,SE-90781"],"affiliations":[{"raw_affiliation_string":"Umeå Unviersity,Department of Computing Science,Umeå,Sweden,SE-90781","institution_ids":["https://openalex.org/I90267481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121184752","display_name":"Erik Elmroth","orcid":null},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Erik Elmroth","raw_affiliation_strings":["Umeå Unviersity,Department of Computing Science,Umeå,Sweden,SE-90781"],"affiliations":[{"raw_affiliation_string":"Umeå Unviersity,Department of Computing Science,Umeå,Sweden,SE-90781","institution_ids":["https://openalex.org/I90267481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5120884408","display_name":"Monowar Bhuyan","orcid":null},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Monowar Bhuyan","raw_affiliation_strings":["Umeå Unviersity,Department of Computing Science,Umeå,Sweden,SE-90781"],"affiliations":[{"raw_affiliation_string":"Umeå Unviersity,Department of Computing Science,Umeå,Sweden,SE-90781","institution_ids":["https://openalex.org/I90267481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048326847"],"corresponding_institution_ids":["https://openalex.org/I90267481"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.8708225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3634","last_page":"3640"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.5979999899864197,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.5979999899864197,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.05920000001788139,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.035999998450279236,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.7993999719619751},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6011000275611877},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4875999987125397},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.47749999165534973},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43540000915527344},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.4226999878883362},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4154999852180481},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.39800000190734863}],"concepts":[{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.7993999719619751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6136000156402588},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6011000275611877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5835000276565552},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4875999987125397},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43540000915527344},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4226999878883362},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4154999852180481},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.39800000190734863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36320000886917114},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.325300008058548},{"id":"https://openalex.org/C150415221","wikidata":"https://www.wikidata.org/wiki/Q40687","display_name":"Robotic arm","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.2824999988079071},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2791000008583069},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27730000019073486},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.2709999978542328},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2687999904155731},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25999999046325684},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W294421534","https://openalex.org/W1999156278","https://openalex.org/W2550075696","https://openalex.org/W2945827727","https://openalex.org/W2962875890","https://openalex.org/W2995022099","https://openalex.org/W3008233947","https://openalex.org/W3042621011","https://openalex.org/W3088158297","https://openalex.org/W3130631955","https://openalex.org/W3202197190","https://openalex.org/W3205933337","https://openalex.org/W4210279759","https://openalex.org/W4221161303","https://openalex.org/W4285505176","https://openalex.org/W4287332481","https://openalex.org/W4319993446","https://openalex.org/W4367146739","https://openalex.org/W4383109250","https://openalex.org/W4401416363","https://openalex.org/W4401416645","https://openalex.org/W4406611600","https://openalex.org/W4411575424","https://openalex.org/W4415708811","https://openalex.org/W4417338227"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"is":[3,52,60],"a":[4,39,85,117],"promising":[5],"machine":[6],"learning":[7],"paradigm":[8],"that":[9,53,59],"enables":[10],"participating":[11],"devices":[12],"to":[13,115,135,143,167],"train":[14,38,136],"privacy-preserved":[15],"and":[16,45,62,66,111,126,140,173],"collaborative":[17],"models.":[18],"FL":[19,87,163],"has":[20],"proven":[21],"its":[22],"benefits":[23],"for":[24,89],"robotic":[25,76,90],"manipulation":[26],"tasks.":[27],"However,":[28],"grasping":[29,175],"tasks":[30],"lack":[31],"exploration":[32],"in":[33,75,79,155],"such":[34],"settings":[35],"where":[36],"robots":[37,114,121,134],"global":[40],"model":[41,152],"without":[42],"moving":[43],"data":[44,47,58,100,109,124],"ensuring":[46],"privacy.":[48],"The":[49],"main":[50],"challenge":[51],"each":[54],"robot":[55],"learns":[56],"from":[57],"nonindependent":[61],"identically":[63],"distributed":[64],"(non-IID)":[65],"of":[67,119,151],"low":[68],"quantity.":[69],"This":[70],"exhibits":[71],"performance":[72,153],"degradation,":[73],"particularly":[74],"grasping.":[77],"Thus,":[78],"this":[80],"work,":[81],"we":[82],"propose":[83],"MTF-Grasp,":[84],"multi-tier":[86],"approach":[88,159],"grasping,":[91],"acknowledging":[92],"the":[93,98,144,149,161,170],"unique":[94],"challenges":[95],"posed":[96],"by":[97,165],"non-IID":[99],"distribution":[101,125],"across":[102,113],"robots,":[103,147],"including":[104],"quantitative":[105],"skewness.":[106],"MTF-Grasp":[107],"harnesses":[108],"quality":[110],"quantity":[112],"select":[116],"set":[118],"\"top-level\"":[120],"with":[122],"better":[123],"higher":[127],"sample":[128],"count.":[129],"It":[130],"then":[131],"utilizes":[132],"top-level":[133],"initial":[137],"seed":[138],"models":[139],"distribute":[141],"them":[142],"remaining":[145],"\"low-level\"":[146],"reducing":[148],"risk":[150],"degradation":[154],"low-level":[156],"robots.":[157],"Our":[158],"outperforms":[160],"conventional":[162],"setup":[164],"up":[166],"8%":[168],"on":[169],"quantity-skewed":[171],"Cornell":[172],"Jacquard":[174],"datasets.":[176]},"counts_by_year":[],"updated_date":"2026-01-29T23:17:01.242718","created_date":"2026-01-29T00:00:00"}