{"id":"https://openalex.org/W3000181076","doi":"https://doi.org/10.1109/ro-man46459.2019.8956326","title":"TeachMe: Three-phase learning framework for robotic motion imitation based on interactive teaching and reinforcement learning","display_name":"TeachMe: Three-phase learning framework for robotic motion imitation based on interactive teaching and reinforcement learning","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W3000181076","doi":"https://doi.org/10.1109/ro-man46459.2019.8956326","mag":"3000181076"},"language":"en","primary_location":{"id":"doi:10.1109/ro-man46459.2019.8956326","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ro-man46459.2019.8956326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","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/A5100400949","display_name":"Taewoo Kim","orcid":"https://orcid.org/0000-0002-7750-3736"},"institutions":[{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taewoo Kim","raw_affiliation_strings":["Department of Computer Software and Engineering, Korea University of Science and Technology, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Software and Engineering, Korea University of Science and Technology, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I88761825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034140846","display_name":"Joo-Haeng Lee","orcid":"https://orcid.org/0000-0002-5788-712X"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joo-Haeng Lee","raw_affiliation_strings":["Human-Robot Interaction Research Group, Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Human-Robot Interaction Research Group, Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9995999932289124,"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/T12290","display_name":"Human Motion and Animation","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7321014404296875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7081268429756165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6812705397605896},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6212117671966553},{"id":"https://openalex.org/keywords/humanoid-robot","display_name":"Humanoid robot","score":0.5860495567321777},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5723785161972046},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.5561022758483887},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.5430055260658264},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.49998950958251953},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4729428291320801},{"id":"https://openalex.org/keywords/robot-kinematics","display_name":"Robot kinematics","score":0.4588291347026825},{"id":"https://openalex.org/keywords/robot-learning","display_name":"Robot learning","score":0.4512086808681488},{"id":"https://openalex.org/keywords/human\u2013robot-interaction","display_name":"Human\u2013robot interaction","score":0.4394940733909607},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.19387459754943848},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.15046250820159912}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7321014404296875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7081268429756165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6812705397605896},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6212117671966553},{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.5860495567321777},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5723785161972046},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.5561022758483887},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.5430055260658264},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.49998950958251953},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4729428291320801},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.4588291347026825},{"id":"https://openalex.org/C188888258","wikidata":"https://www.wikidata.org/wiki/Q7353390","display_name":"Robot learning","level":4,"score":0.4512086808681488},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.4394940733909607},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.19387459754943848},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.15046250820159912},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ro-man46459.2019.8956326","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ro-man46459.2019.8956326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W187005120","https://openalex.org/W1486649854","https://openalex.org/W1517823811","https://openalex.org/W1550621568","https://openalex.org/W1757796397","https://openalex.org/W1959608418","https://openalex.org/W1986014385","https://openalex.org/W1997302797","https://openalex.org/W2048394824","https://openalex.org/W2082511574","https://openalex.org/W2097651961","https://openalex.org/W2099471712","https://openalex.org/W2101032778","https://openalex.org/W2125220306","https://openalex.org/W2126172323","https://openalex.org/W2130726249","https://openalex.org/W2151140424","https://openalex.org/W2157837575","https://openalex.org/W2158794687","https://openalex.org/W2166302491","https://openalex.org/W2184965786","https://openalex.org/W2187089797","https://openalex.org/W2257979135","https://openalex.org/W2522489477","https://openalex.org/W2592538810","https://openalex.org/W2735700496","https://openalex.org/W2736601468","https://openalex.org/W2754362686","https://openalex.org/W2788244128","https://openalex.org/W2788807549","https://openalex.org/W2792089292","https://openalex.org/W2796290181","https://openalex.org/W2800549527","https://openalex.org/W2869375357","https://openalex.org/W2890486280","https://openalex.org/W2894846593","https://openalex.org/W2899771611","https://openalex.org/W2908684875","https://openalex.org/W2962747693","https://openalex.org/W2963634205","https://openalex.org/W2963669336","https://openalex.org/W2963802910","https://openalex.org/W2964134613","https://openalex.org/W3104515094","https://openalex.org/W3151718294","https://openalex.org/W4298857966","https://openalex.org/W4320013936","https://openalex.org/W6629028937","https://openalex.org/W6637967152","https://openalex.org/W6640963894","https://openalex.org/W6741002519","https://openalex.org/W6744448386","https://openalex.org/W6755013099","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W4293926484","https://openalex.org/W2163555676","https://openalex.org/W4390481035","https://openalex.org/W4386128912","https://openalex.org/W2776995446","https://openalex.org/W1989753795","https://openalex.org/W3133699834","https://openalex.org/W2809775952","https://openalex.org/W2542622692"],"abstract_inverted_index":{"Motion":[0],"imitation":[1,161,239,253],"is":[2,30,207],"a":[3,8,12,16,73,83,90,121,130,142,159,212],"fundamental":[4],"communication":[5],"skill":[6,162],"for":[7,114,120,129,221,237,256],"robot;":[9],"especially,":[10],"as":[11,51],"nonverbal":[13],"interaction":[14],"with":[15],"human.":[17],"Owing":[18],"to":[19,32,88,93,208,229],"kinematic":[20],"configuration":[21],"differences":[22],"between":[23,37],"the":[24,27,34,38,139,155,168,172,175,185,198,202,230,248,252],"human":[25,56,97,143],"and":[26,125,145,259],"robot,":[28],"it":[29,206],"challenging":[31],"determine":[33],"appropriate":[35],"mapping":[36,67],"two":[39,119],"pose":[40,98],"domains.":[41],"Moreover,":[42],"technical":[43],"limitations":[44],"while":[45],"extracting":[46],"3D":[47],"motion":[48,57,64,70,178,222],"details,":[49],"such":[50],"wrist":[52],"joint":[53],"movements":[54],"from":[55,96,101,263],"videos,":[58],"results":[59,245],"in":[60,63,184,201,224,240],"significant":[61],"challenges":[62],"retargeting.":[65],"Explicit":[66],"over":[68],"different":[69],"domains":[71],"indicates":[72],"considerably":[74],"inefficient":[75],"solution.":[76],"To":[77],"solve":[78],"these":[79],"problems,":[80],"we":[81],"propose":[82],"three-phase":[84],"reinforcement":[85,123,132,164],"learning":[86,105,115,165],"scheme":[87,106],"enable":[89],"NAO":[91,156],"robot":[92,146,157,176],"learn":[94],"motions":[95,140,261],"skeletons":[99],"extracted":[100],"video":[102],"inputs.":[103],"Our":[104],"consists":[107],"of":[108,138,141,197,216,233],"three":[109,128,226],"phases:":[110],"(i)":[111],"phase":[112,118,127,135,153,225,241],"one":[113],"preparation,":[116],"(ii)":[117],"simulation-based":[122],"learning,":[124],"(iii)":[126],"human-in-the-loop-based":[131],"learning.":[133],"In":[134,152,171],"one,":[136],"embeddings":[137],"skeleton":[144],"are":[147,219],"learned":[148,169],"by":[149,188],"an":[150],"autoencoder.":[151],"two,":[154],"learns":[158,177],"rough":[160],"using":[163],"that":[166,180,211,247],"translates":[167],"embeddings.":[170],"last":[173],"phase,":[174],"details":[179,223],"were":[181],"not":[182],"considered":[183],"previous":[186,203],"phases":[187],"interactively":[189],"setting":[190],"rewards":[191],"based":[192],"on":[193],"direct":[194],"teaching":[195],"instead":[196],"method":[199,250],"used":[200],"phase.":[204],"Especially,":[205],"be":[209],"noted":[210],"relatively":[213],"smaller":[214],"number":[215],"interactive":[217],"inputs":[218],"required":[220,236],"when":[227],"compared":[228],"large":[231],"volume":[232],"training":[234],"sets":[235],"overall":[238],"two.":[242],"The":[243],"experimental":[244],"demonstrate":[246],"proposed":[249],"improves":[251],"skills":[254],"efficiently":[255],"hand":[257],"waving":[258],"saluting":[260],"obtained":[262],"NTU-DB.":[264]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}