{"id":"https://openalex.org/W2561515991","doi":"https://doi.org/10.1109/tase.2016.2624279","title":"Human Intention Inference Using Expectation-Maximization Algorithm With Online Model Learning","display_name":"Human Intention Inference Using Expectation-Maximization Algorithm With Online Model Learning","publication_year":2016,"publication_date":"2016-12-27","ids":{"openalex":"https://openalex.org/W2561515991","doi":"https://doi.org/10.1109/tase.2016.2624279","mag":"2561515991"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2016.2624279","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2016.2624279","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Transactions on Automation Science and Engineering","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/A5087370510","display_name":"Harish Ravichandar","orcid":"https://orcid.org/0000-0002-6635-2637"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Harish Chaandar Ravichandar","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076083833","display_name":"Ashwin P. Dani","orcid":"https://orcid.org/0000-0002-7091-5607"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashwin P. Dani","raw_affiliation_strings":["Department of Electrical and Computer Engineering and the Management and Engineering for Manufacturing Program, University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and the Management and Engineering for Manufacturing Program, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087370510"],"corresponding_institution_ids":["https://openalex.org/I140172145"],"apc_list":null,"apc_paid":null,"fwci":5.4162,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.95931623,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"14","issue":"2","first_page":"855","last_page":"868"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9987999796867371,"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":0.9987999796867371,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6211962699890137},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6074846386909485},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5572693943977356},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48519614338874817},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.46532532572746277},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4650837779045105},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46001100540161133},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4517109990119934},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4406149983406067},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.41534319519996643},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39682167768478394},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3861628770828247},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.28034287691116333},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21285051107406616}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6211962699890137},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6074846386909485},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5572693943977356},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48519614338874817},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.46532532572746277},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4650837779045105},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46001100540161133},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4517109990119934},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4406149983406067},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.41534319519996643},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39682167768478394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3861628770828247},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.28034287691116333},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21285051107406616},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2016.2624279","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2016.2624279","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W46490633","https://openalex.org/W194242946","https://openalex.org/W1480774840","https://openalex.org/W1483858097","https://openalex.org/W1484536156","https://openalex.org/W1496321300","https://openalex.org/W1528932438","https://openalex.org/W1955948120","https://openalex.org/W1965660319","https://openalex.org/W1969029184","https://openalex.org/W1987616874","https://openalex.org/W1988242845","https://openalex.org/W1992461594","https://openalex.org/W1998683434","https://openalex.org/W1999657641","https://openalex.org/W2000982104","https://openalex.org/W2001865981","https://openalex.org/W2005676786","https://openalex.org/W2008458232","https://openalex.org/W2023032873","https://openalex.org/W2024479254","https://openalex.org/W2047197161","https://openalex.org/W2049633694","https://openalex.org/W2077677219","https://openalex.org/W2082581021","https://openalex.org/W2099019320","https://openalex.org/W2110667948","https://openalex.org/W2115941714","https://openalex.org/W2118760499","https://openalex.org/W2119004998","https://openalex.org/W2124218221","https://openalex.org/W2124609748","https://openalex.org/W2126958497","https://openalex.org/W2133104731","https://openalex.org/W2146055337","https://openalex.org/W2210365848","https://openalex.org/W2217354111","https://openalex.org/W2268284457","https://openalex.org/W2293288132","https://openalex.org/W2295362572","https://openalex.org/W2296494999","https://openalex.org/W2318055712","https://openalex.org/W2403419699","https://openalex.org/W2911546748","https://openalex.org/W2980103447","https://openalex.org/W3105729849","https://openalex.org/W4205559380","https://openalex.org/W4240592325","https://openalex.org/W4376549770","https://openalex.org/W6628869256","https://openalex.org/W6648315218","https://openalex.org/W6677571061","https://openalex.org/W6712834864"],"related_works":["https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W4323768008","https://openalex.org/W1508899372","https://openalex.org/W4248382324","https://openalex.org/W4360995134","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W3023605104","https://openalex.org/W2383578611"],"abstract_inverted_index":{"An":[0],"algorithm":[1,77,90,138,147,172],"called":[2],"adaptive-neural-intention":[3],"estimator":[4],"(ANIE)":[5],"is":[6,62,78,91,139,173],"presented":[7],"to":[8,80,93,95],"infer":[9,81],"the":[10,20,33,71,96,99,103,106,110,163,176,189],"intent":[11],"of":[12,36,113,119,131],"a":[13,23,66,129,183],"human":[14,82,115],"operator's":[15],"arm":[16,100],"movements":[17],"based":[18],"on":[19,70,122,188],"observations":[21],"from":[22,125],"3-D":[24,40],"camera":[25],"sensor":[26],"(Microsoft":[27],"Kinect).":[28],"Intentions":[29],"are":[30,47,134],"modeled":[31,48],"as":[32,57],"goal":[34,107],"locations":[35],"reaching":[37,132],"motions":[38,133],"in":[39,98,162],"space.":[41],"Human":[42],"arm's":[43],"nonlinear":[44,52],"motion":[45,101,104],"dynamics":[46],"using":[49,65,154,182],"an":[50,74,85,142,149],"unknown":[51,60],"function":[53],"with":[54,141,175],"intentions":[55],"represented":[56],"parameters.":[58],"The":[59,117,136,170],"model":[61,88,146],"learned":[63,72],"by":[64,153],"neural":[67],"network.":[68],"Based":[69],"model,":[73],"approximate":[75],"expectation-maximization":[76],"developed":[79,92],"intentions.":[83],"Furthermore,":[84],"identifier-based":[86],"online":[87],"learning":[89],"adapt":[94],"variations":[97],"dynamics,":[102],"trajectory,":[105],"locations,":[108],"and":[109,148,159,165,179],"initial":[111],"conditions":[112],"different":[114,126],"subjects.":[116],"results":[118],"experiments":[120],"conducted":[121],"data":[123,157,160,191],"obtained":[124],"users":[127],"performing":[128],"variety":[130],"presented.":[135],"ANIE":[137,171],"compared":[140,174],"unsupervised":[143],"Gaussian":[144],"mixture":[145],"Euclidean":[150],"distance-based":[151],"approach":[152],"Cornell's":[155],"CAD-120":[156,190],"set":[158],"collected":[161],"Robotics":[164],"Controls":[166],"Laboratoy":[167],"at":[168],"UConn.":[169],"inverse":[177],"LQR":[178],"ATCRF":[180],"algorithms":[181],"labeling":[184],"task":[185],"carried":[186],"out":[187],"set.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}