{"id":"https://openalex.org/W4409640608","doi":"https://doi.org/10.1109/lra.2025.3562793","title":"Event-Driven Force Measurement of a Variable-Stiffness Robotic Finger Using Masked Autoencoder Pre-Training","display_name":"Event-Driven Force Measurement of a Variable-Stiffness Robotic Finger Using Masked Autoencoder Pre-Training","publication_year":2025,"publication_date":"2025-04-21","ids":{"openalex":"https://openalex.org/W4409640608","doi":"https://doi.org/10.1109/lra.2025.3562793"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2025.3562793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3562793","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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":null,"display_name":"Qianyu Guo","orcid":"https://orcid.org/0009-0004-5434-5044"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qianyu Guo","raw_affiliation_strings":["School of Engineering Technology, Purdue University, West Lafayette, IN, USA","School of Engineering Technology, Purdue University, USA"],"raw_orcid":"https://orcid.org/0009-0004-5434-5044","affiliations":[{"raw_affiliation_string":"School of Engineering Technology, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of Engineering Technology, Purdue University, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103247375","display_name":"Yawen Lu","orcid":"https://orcid.org/0000-0001-8046-3045"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yawen Lu","raw_affiliation_strings":["Computer Graphics Technology Department, Purdue University, West Lafayette, IN, USA","Computer Graphics Technology Department, Purdue University, USA"],"raw_orcid":"https://orcid.org/0000-0001-8046-3045","affiliations":[{"raw_affiliation_string":"Computer Graphics Technology Department, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Computer Graphics Technology Department, Purdue University, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102862564","display_name":"Jiaming Fu","orcid":"https://orcid.org/0009-0006-0456-5115"},"institutions":[{"id":"https://openalex.org/I83683471","display_name":"University of West Florida","ror":"https://ror.org/002w4zy91","country_code":"US","type":"education","lineage":["https://openalex.org/I83683471"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaming Fu","raw_affiliation_strings":["Mechanical Engineering Department, University of West Florida, Pensacola, FL, USA","Mechanical Engineering Department, the University of West Florida, USA"],"raw_orcid":"https://orcid.org/0009-0006-0456-5115","affiliations":[{"raw_affiliation_string":"Mechanical Engineering Department, University of West Florida, Pensacola, FL, USA","institution_ids":["https://openalex.org/I83683471"]},{"raw_affiliation_string":"Mechanical Engineering Department, the University of West Florida, USA","institution_ids":["https://openalex.org/I83683471"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019475373","display_name":"Dongming Gan","orcid":"https://orcid.org/0000-0001-5327-1902"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongming Gan","raw_affiliation_strings":["School of Engineering Technology, Purdue University, West Lafayette, IN, USA","School of Engineering Technology, Purdue University, USA"],"raw_orcid":"https://orcid.org/0000-0001-5327-1902","affiliations":[{"raw_affiliation_string":"School of Engineering Technology, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of Engineering Technology, Purdue University, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.6013,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64967712,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"10","issue":"6","first_page":"5831","last_page":"5838"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9907000064849854,"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"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9907000064849854,"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"}},{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7308342456817627},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5537626147270203},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5383217930793762},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.4760986566543579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4583224356174469},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4522734582424164},{"id":"https://openalex.org/keywords/stiffness","display_name":"Stiffness","score":0.4428534507751465},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4320601224899292},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.27688470482826233},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2433069348335266},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19151851534843445},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15511220693588257},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11030277609825134},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.09215125441551208}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7308342456817627},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5537626147270203},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5383217930793762},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.4760986566543579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4583224356174469},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4522734582424164},{"id":"https://openalex.org/C2779372316","wikidata":"https://www.wikidata.org/wiki/Q569057","display_name":"Stiffness","level":2,"score":0.4428534507751465},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4320601224899292},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.27688470482826233},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2433069348335266},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19151851534843445},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15511220693588257},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11030277609825134},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.09215125441551208},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2025.3562793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3562793","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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/G362010944","display_name":null,"funder_award_id":"CMMI-2131711","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W2014673260","https://openalex.org/W2037924503","https://openalex.org/W2123623965","https://openalex.org/W2411278854","https://openalex.org/W2787667999","https://openalex.org/W2996290406","https://openalex.org/W2998748860","https://openalex.org/W3004623551","https://openalex.org/W3040838455","https://openalex.org/W3047911145","https://openalex.org/W3092588809","https://openalex.org/W3102407952","https://openalex.org/W3138516171","https://openalex.org/W3139885827","https://openalex.org/W3159481202","https://openalex.org/W3178872387","https://openalex.org/W3196288474","https://openalex.org/W3200203756","https://openalex.org/W3206328020","https://openalex.org/W3213517261","https://openalex.org/W4285124932","https://openalex.org/W4303981207","https://openalex.org/W4312397461","https://openalex.org/W4312443924","https://openalex.org/W4313156423","https://openalex.org/W4317796334","https://openalex.org/W4318586184","https://openalex.org/W4321600687","https://openalex.org/W4322731057","https://openalex.org/W4377971350","https://openalex.org/W4386076206","https://openalex.org/W4386076238","https://openalex.org/W4388874040","https://openalex.org/W4389352616","https://openalex.org/W4389623024","https://openalex.org/W4390873350","https://openalex.org/W4392405643","https://openalex.org/W4401539044","https://openalex.org/W4402916931","https://openalex.org/W6861387779","https://openalex.org/W6862914174","https://openalex.org/W6869177682","https://openalex.org/W6869537869","https://openalex.org/W6873171758"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866"],"abstract_inverted_index":{"Force":[0],"feedback":[1],"in":[2,46,78,135],"compliant":[3,79,179],"robotic":[4],"grippers":[5],"is":[6],"essential":[7],"for":[8,111,170],"precise":[9,184],"manipulation":[10],"tasks":[11],"but":[12],"remains":[13],"challenging":[14],"because":[15],"irregular":[16],"deformation":[17],"of":[18],"soft":[19],"materials":[20],"renders":[21],"traditional":[22],"sensor":[23],"integration":[24],"impractical.":[25],"Event":[26],"camera":[27,76],"has":[28],"emerged":[29],"as":[30],"a":[31,47,62,70,88,96,117,130],"powerful":[32],"alternative":[33],"to":[34,41,73,121,139,177],"conventional":[35],"vision":[36],"sensors":[37],"through":[38],"their":[39],"ability":[40],"capture":[42],"only":[43],"temporal":[44],"changes":[45],"scene,":[48],"thereby":[49],"significantly":[50],"reducing":[51],"data":[52,77],"redundancy":[53],"and":[54,94,153],"processing":[55],"overhead.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60,85],"introduce":[61],"novel":[63],"vision-based":[64],"force":[65,124,185],"prediction":[66],"framework":[67,120],"that":[68,182],"employs":[69],"Mamba-Like":[71],"architecture":[72],"process":[74],"event":[75,104],"grippers.":[80],"To":[81],"validate":[82],"our":[83],"approach,":[84],"have":[86],"developed":[87],"custom":[89],"gripper":[90,158],"with":[91,116],"variable":[92],"stiffness":[93],"created":[95],"comprehensive":[97],"dataset":[98],"comprising":[99],"over":[100],"<italic":[101,131],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[102,132],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">9,000</i>":[103],"frames.":[105],"Our":[106,164],"methodology":[107],"combines":[108],"self-supervised":[109],"pre-training":[110],"learning":[112],"rich":[113],"feature":[114],"representations":[115],"Mamba-like":[118],"regression":[119],"achieve":[122],"accurate":[123],"prediction.":[125],"The":[126],"proposed":[127],"method":[128],"demonstrates":[129],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0.14</i>":[133],"improvement":[134],"RMSE":[136],"when":[137],"compared":[138],"existing":[140],"Vision":[141],"Transformer":[142],"approaches.":[143],"Through":[144],"extensive":[145],"experimental":[146],"validation-including":[147],"real-time":[148],"performance":[149,168],"analysis,":[150],"ablation":[151],"studies,":[152],"generalization":[154],"tests":[155],"across":[156],"various":[157],"configurations-we":[159],"demonstrate":[160],"the":[161],"framework's":[162],"effectiveness.":[163],"results":[165],"indicate":[166],"robust":[167],"suitable":[169],"practical":[171],"industrial":[172],"applications,":[173],"suggesting":[174],"potential":[175],"extensions":[176],"other":[178],"robotics":[180],"applications":[181],"require":[183],"estimation.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}