{"id":"https://openalex.org/W4312303763","doi":"https://doi.org/10.1109/icdl53763.2022.9962208","title":"Don\u2019t Forget to Buy Milk: Contextually Aware Grocery Reminder Household Robot","display_name":"Don\u2019t Forget to Buy Milk: Contextually Aware Grocery Reminder Household Robot","publication_year":2022,"publication_date":"2022-09-12","ids":{"openalex":"https://openalex.org/W4312303763","doi":"https://doi.org/10.1109/icdl53763.2022.9962208"},"language":"en","primary_location":{"id":"doi:10.1109/icdl53763.2022.9962208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdl53763.2022.9962208","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Development and Learning (ICDL)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5072603093","display_name":"Ali Ayub","orcid":"https://orcid.org/0000-0001-9458-477X"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ali Ayub","raw_affiliation_strings":["University of Waterloo,Department of Electrical and Computer Engineering,Waterloo,ON,Canada,N2T2J3"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Department of Electrical and Computer Engineering,Waterloo,ON,Canada,N2T2J3","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048759955","display_name":"Chrystopher L. Nehaniv","orcid":"https://orcid.org/0000-0002-7807-1875"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chrystopher L. Nehaniv","raw_affiliation_strings":["University of Waterloo,Department of Systems Design Engineering,Waterloo,ON,Canada,N2T2J3","Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Department of Systems Design Engineering,Waterloo,ON,Canada,N2T2J3","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059371010","display_name":"Kerstin Dautenhahn","orcid":"https://orcid.org/0000-0002-9263-3897"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kerstin Dautenhahn","raw_affiliation_strings":["University of Waterloo,Department of Electrical and Computer Engineering,Waterloo,ON,Canada,N2T2J3","Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Department of Electrical and Computer Engineering,Waterloo,ON,Canada,N2T2J3","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"299","last_page":"306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9911999702453613,"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":0.9911999702453613,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9894000291824341,"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":0.9843000173568726,"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/computer-science","display_name":"Computer science","score":0.7400881052017212},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.6636606454849243},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6578089594841003},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5295649170875549},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5247169733047485},{"id":"https://openalex.org/keywords/cognitive-architecture","display_name":"Cognitive architecture","score":0.4803784489631653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46410664916038513},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.380415678024292},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1070629358291626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7400881052017212},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.6636606454849243},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6578089594841003},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5295649170875549},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5247169733047485},{"id":"https://openalex.org/C20854674","wikidata":"https://www.wikidata.org/wiki/Q4386060","display_name":"Cognitive architecture","level":3,"score":0.4803784489631653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46410664916038513},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.380415678024292},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1070629358291626},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdl53763.2022.9962208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdl53763.2022.9962208","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Development and Learning (ICDL)","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":30,"referenced_works":["https://openalex.org/W1585745932","https://openalex.org/W1861492603","https://openalex.org/W1969230772","https://openalex.org/W2015563892","https://openalex.org/W2028912620","https://openalex.org/W2058960948","https://openalex.org/W2102960359","https://openalex.org/W2117539524","https://openalex.org/W2170014483","https://openalex.org/W2194775991","https://openalex.org/W2296755157","https://openalex.org/W2561529111","https://openalex.org/W2599577839","https://openalex.org/W2604988916","https://openalex.org/W2614653677","https://openalex.org/W2948970881","https://openalex.org/W2954219865","https://openalex.org/W2963037989","https://openalex.org/W2989785064","https://openalex.org/W3005807552","https://openalex.org/W3015309906","https://openalex.org/W3043615800","https://openalex.org/W3158301146","https://openalex.org/W3199661966","https://openalex.org/W3201480814","https://openalex.org/W3203003214","https://openalex.org/W4206581676","https://openalex.org/W4300402905","https://openalex.org/W6766374549","https://openalex.org/W6794969854"],"related_works":["https://openalex.org/W8302103","https://openalex.org/W2588198209","https://openalex.org/W1909006023","https://openalex.org/W3200723557","https://openalex.org/W4205824991","https://openalex.org/W4312713546","https://openalex.org/W3171631314","https://openalex.org/W2362195430","https://openalex.org/W2162577226","https://openalex.org/W2050312972"],"abstract_inverted_index":{"Assistive":[0],"robots":[1],"operating":[2],"in":[3,12,133],"household":[4,57,79],"environments":[5],"would":[6],"require":[7],"items":[8,22,76,106,176],"to":[9,15,32,50,71,116,152,172],"be":[10],"available":[11],"the":[13,25,34,68,78,108,119,126,148,169],"house":[14],"perform":[16],"assistive":[17,26],"tasks.":[18],"However,":[19],"when":[20],"these":[21],"run":[23],"out,":[24],"robot":[27,49,130,149,165],"must":[28],"remind":[29],"its":[30,61,162],"user":[31,113],"buy":[33],"missing":[35,75,105,175],"items.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"present":[41],"a":[42,48,56,81,100,111,134],"computational":[43],"architecture":[44,64,87,122],"that":[45,147],"can":[46,65,150,166],"allow":[47],"learn":[51],"personalized":[52],"contextual":[53,157],"knowledge":[54,70,158,171],"of":[55,84,95],"through":[58,159],"interactions":[59,160],"with":[60,118,125,138,161],"user.":[62,120,163],"The":[63,86,121,164],"then":[66],"use":[67,168],"learned":[69,170],"make":[72],"predictions":[73],"about":[74],"from":[77,107],"over":[80,177],"long":[82],"period":[83],"time.":[85],"integrates":[88],"state-of-the-art":[89],"perceptual":[90,187],"learning":[91,156],"algorithms,":[92],"cognitive":[93],"models":[94],"memory":[96],"encoding":[97],"and":[98,110,131,141,180,186],"learning,":[99],"reasoning":[101],"module":[102],"for":[103],"predicting":[104],"household,":[109],"graphical":[112],"interface":[114],"(GUI)":[115],"interact":[117],"is":[123,182],"integrated":[124],"Fetch":[127],"mobile":[128],"manipulator":[129],"validated":[132],"large":[135],"indoor":[136],"environment":[137,154],"multiple":[139,178],"contexts":[140],"objects.":[142],"Our":[143],"experimental":[144],"results":[145],"show":[146],"adapt":[151],"an":[153],"by":[155],"also":[167],"correctly":[173],"predict":[174],"weeks":[179],"it":[181],"robust":[183],"against":[184],"sensory":[185],"errors.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
