{"id":"https://openalex.org/W2558355904","doi":"https://doi.org/10.1109/lra.2016.2633383","title":"Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning","display_name":"Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning","publication_year":2016,"publication_date":"2016-11-29","ids":{"openalex":"https://openalex.org/W2558355904","doi":"https://doi.org/10.1109/lra.2016.2633383","mag":"2558355904"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2016.2633383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2016.2633383","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":"https://openalex.org/A5108730044","display_name":"Pin-Chu Yang","orcid":null},"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":true,"raw_author_name":"Pin-Chu Yang","raw_affiliation_strings":["Artificial Intelligence Research Center, Tsukuba, Japan","Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Tsukuba, Japan","institution_ids":[]},{"raw_affiliation_string":"Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003977701","display_name":"Kazuma Sasaki","orcid":"https://orcid.org/0000-0002-4586-801X"},"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":"Kazuma Sasaki","raw_affiliation_strings":["Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042849965","display_name":"Kanata Suzuki","orcid":"https://orcid.org/0000-0001-7122-7649"},"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":"Kanata Suzuki","raw_affiliation_strings":["Artificial Intelligence Research Center, Tsukuba, Japan","Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Tsukuba, Japan","institution_ids":[]},{"raw_affiliation_string":"Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010195602","display_name":"Kei Kase","orcid":"https://orcid.org/0000-0003-4009-5254"},"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":"Kei Kase","raw_affiliation_strings":["Artificial Intelligence Research Center, Tsukuba, Japan","Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Tsukuba, Japan","institution_ids":[]},{"raw_affiliation_string":"Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","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":["Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","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":["Artificial Intelligence Research Center, Tsukuba, Japan","Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Tsukuba, Japan","institution_ids":[]},{"raw_affiliation_string":"Department of Intermedia Art and Science, School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5108730044"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":17.3085,"has_fulltext":false,"cited_by_count":235,"citation_normalized_percentile":{"value":0.99376967,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"2","issue":"2","first_page":"397","last_page":"403"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T10868","display_name":"Soft Robotics and Applications","score":0.989799976348877,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9896000027656555,"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/humanoid-robot","display_name":"Humanoid robot","score":0.7861934900283813},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7492165565490723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7159337401390076},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6600065231323242},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6154634952545166},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5558616518974304},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.489167720079422},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48551297187805176},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47960197925567627},{"id":"https://openalex.org/keywords/teleoperation","display_name":"Teleoperation","score":0.47128573060035706},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45148593187332153},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33624422550201416},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.172915518283844}],"concepts":[{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.7861934900283813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7492165565490723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7159337401390076},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6600065231323242},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6154634952545166},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5558616518974304},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.489167720079422},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48551297187805176},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47960197925567627},{"id":"https://openalex.org/C161759796","wikidata":"https://www.wikidata.org/wiki/Q3982902","display_name":"Teleoperation","level":3,"score":0.47128573060035706},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45148593187332153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33624422550201416},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.172915518283844},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C129307140","wikidata":"https://www.wikidata.org/wiki/Q6795880","display_name":"Maximum bubble pressure method","level":3,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2016.2633383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2016.2633383","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":[{"id":"https://metadata.un.org/sdg/8","score":0.550000011920929,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308359","display_name":"AIST Foundation","ror":"https://ror.org/02yn0z735"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1589481967","https://openalex.org/W1731081199","https://openalex.org/W1885185971","https://openalex.org/W1982920857","https://openalex.org/W1999156278","https://openalex.org/W2022074612","https://openalex.org/W2048060899","https://openalex.org/W2088335308","https://openalex.org/W2092231503","https://openalex.org/W2117743276","https://openalex.org/W2155007355","https://openalex.org/W2201912979","https://openalex.org/W2618530766","https://openalex.org/W2626581429","https://openalex.org/W2962736495","https://openalex.org/W2964121744","https://openalex.org/W2964161785","https://openalex.org/W6631190155","https://openalex.org/W6682849425","https://openalex.org/W6697071109"],"related_works":["https://openalex.org/W4315881361","https://openalex.org/W4318953217","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,8,16,49,54,58,62,86,112,124,177],"practical":[3],"state-of-the-art":[4],"method":[5],"to":[6,27,82,148],"develop":[7],"machine-learning-based":[9],"humanoid":[10,140],"robot":[11,125,141],"that":[12,79],"can":[13],"work":[14],"as":[15,144],"production":[17],"line":[18],"worker.":[19],"The":[20,45,137,153],"proposed":[21,46,99,151],"approach":[22,47],"provides":[23,57],"an":[24,145],"intuitive":[25],"way":[26],"collect":[28],"data":[29],"and":[30,42,56,108,111,133,161],"exhibits":[31],"the":[32,98,121,129,150,170,182],"following":[33],"characteristics:":[34],"task":[35,38,73,126,156],"performing":[36],"capability,":[37],"reiteration":[39],"ability,":[40],"generalizability,":[41],"easy":[43],"applicability.":[44],"utilizes":[48],"real-time":[50],"user":[51],"interface":[52],"with":[53,85,158,173],"monitor":[55],"first-person":[59],"perspective":[60],"using":[61],"head-mounted":[63],"display.":[64],"Through":[65],"this":[66],"interface,":[67],"teleoperation":[68],"is":[69,94,142],"used":[70,143],"for":[71,77,167,181],"collecting":[72],"operating":[74],"data,":[75],"especially":[76],"tasks":[78],"are":[80],"difficult":[81],"be":[83],"applied":[84],"conventional":[87],"method.":[88],"A":[89,101],"two-phase":[90],"deep":[91,102,115],"learning":[92],"model":[93,172],"also":[95],"utilized":[96],"in":[97],"approach.":[100],"convolutional":[103],"autoencoder":[104],"extracts":[105],"images":[106],"features":[107,132],"reconstructs":[109],"images,":[110],"fully":[113],"connected":[114],"time":[116],"delay":[117],"neural":[118],"network":[119],"learns":[120],"dynamics":[122],"of":[123],"process":[127],"from":[128],"extracted":[130],"image":[131],"motion":[134],"angle":[135],"signals.":[136],"\u201cNextage":[138],"Open\u201d":[139],"experimental":[146],"platform":[147],"evaluate":[149],"model.":[152],"object":[154,183],"folding":[155,184],"utilizing":[157],"35":[159],"trained":[160,171],"5":[162],"untrained":[163],"sensory":[164],"motor":[165],"sequences":[166],"test.":[168],"Testing":[169],"online":[174],"generation":[175],"demonstrates":[176],"77.8%":[178],"success":[179],"rate":[180],"task.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":43},{"year":2020,"cited_by_count":34},{"year":2019,"cited_by_count":32},{"year":2018,"cited_by_count":23},{"year":2017,"cited_by_count":9}],"updated_date":"2026-03-15T09:29:46.208133","created_date":"2025-10-10T00:00:00"}
