{"id":"https://openalex.org/W3091304796","doi":"https://doi.org/10.1109/icra40945.2020.9196642","title":"Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning","display_name":"Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3091304796","doi":"https://doi.org/10.1109/icra40945.2020.9196642","mag":"3091304796"},"language":"en","primary_location":{"id":"doi:10.1109/icra40945.2020.9196642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-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/A5100379448","display_name":"Tianyu Li","orcid":"https://orcid.org/0000-0002-9431-2501"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyu Li","raw_affiliation_strings":["Facebook, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083548887","display_name":"Nathan Lambert","orcid":"https://orcid.org/0000-0002-9997-6817"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan Lambert","raw_affiliation_strings":["Work done during an internship at Facebook AI Research, University of California, Berkeley, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Work done during an internship at Facebook AI Research, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002235575","display_name":"Roberto Calandra","orcid":"https://orcid.org/0000-0001-9430-8433"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roberto Calandra","raw_affiliation_strings":["Facebook, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071976030","display_name":"Franziska Meier","orcid":"https://orcid.org/0000-0003-1640-4619"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Franziska Meier","raw_affiliation_strings":["Facebook, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007198769","display_name":"Akshara Rai","orcid":"https://orcid.org/0009-0005-5767-9848"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Akshara Rai","raw_affiliation_strings":["Facebook, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.3331,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.95320356,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"413","last_page":"419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9991000294685364,"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/T10879","display_name":"Robotic Locomotion and Control","score":0.9990000128746033,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9937999844551086,"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":0.7615844011306763},{"id":"https://openalex.org/keywords/hexapod","display_name":"Hexapod","score":0.7425903677940369},{"id":"https://openalex.org/keywords/scratch","display_name":"Scratch","score":0.7244678735733032},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7155806422233582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5611887574195862},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5241251587867737},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5010778903961182},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4408773183822632},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4330917298793793},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.421808123588562},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4178868234157562},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34309154748916626}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7615844011306763},{"id":"https://openalex.org/C136434205","wikidata":"https://www.wikidata.org/wiki/Q3437269","display_name":"Hexapod","level":3,"score":0.7425903677940369},{"id":"https://openalex.org/C2781235140","wikidata":"https://www.wikidata.org/wiki/Q275131","display_name":"Scratch","level":2,"score":0.7244678735733032},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7155806422233582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5611887574195862},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5241251587867737},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5010778903961182},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4408773183822632},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4330917298793793},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.421808123588562},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4178868234157562},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34309154748916626},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra40945.2020.9196642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1502718064","https://openalex.org/W1738827650","https://openalex.org/W1771410628","https://openalex.org/W1978956894","https://openalex.org/W1999272004","https://openalex.org/W2056223738","https://openalex.org/W2071444114","https://openalex.org/W2081700430","https://openalex.org/W2088038240","https://openalex.org/W2109910161","https://openalex.org/W2121863487","https://openalex.org/W2127188258","https://openalex.org/W2132037810","https://openalex.org/W2198582666","https://openalex.org/W2460299708","https://openalex.org/W2498991332","https://openalex.org/W2523728418","https://openalex.org/W2606788132","https://openalex.org/W2694031977","https://openalex.org/W2726187156","https://openalex.org/W2739330054","https://openalex.org/W2765602917","https://openalex.org/W2776302298","https://openalex.org/W2793732783","https://openalex.org/W2900879308","https://openalex.org/W2904246096","https://openalex.org/W2907537824","https://openalex.org/W2909331752","https://openalex.org/W2911087563","https://openalex.org/W2937555108","https://openalex.org/W2961987377","https://openalex.org/W2963161674","https://openalex.org/W2963184939","https://openalex.org/W2963536429","https://openalex.org/W2963960193","https://openalex.org/W2964001908","https://openalex.org/W2964227312","https://openalex.org/W2968717280","https://openalex.org/W2970990801","https://openalex.org/W2977481643","https://openalex.org/W3029509103","https://openalex.org/W3031547186","https://openalex.org/W3101264727","https://openalex.org/W4288348579","https://openalex.org/W4298206671","https://openalex.org/W4300799055","https://openalex.org/W6638018090","https://openalex.org/W6727349600","https://openalex.org/W6736435945","https://openalex.org/W6740222838","https://openalex.org/W6740801417","https://openalex.org/W6744935223","https://openalex.org/W6751494529","https://openalex.org/W6756168450","https://openalex.org/W6757380569","https://openalex.org/W6757592117","https://openalex.org/W6761392374","https://openalex.org/W6765121789","https://openalex.org/W6765752869","https://openalex.org/W6768511085","https://openalex.org/W6841393079"],"related_works":["https://openalex.org/W2146302595","https://openalex.org/W613729187","https://openalex.org/W138543751","https://openalex.org/W2789574804","https://openalex.org/W2114803124","https://openalex.org/W2063353256","https://openalex.org/W123722128","https://openalex.org/W4390269031","https://openalex.org/W4389787393","https://openalex.org/W3097667865"],"abstract_inverted_index":{"Learning":[0],"to":[1,3,54,99,101,103,107],"locomote":[2],"arbitrary":[4,104],"goals":[5,105],"on":[6,32,71,118,122],"hardware":[7,126],"remains":[8],"a":[9,20,72,91,123],"challenging":[10],"problem":[11,39],"for":[12],"reinforcement":[13],"learning.":[14],"In":[15],"this":[16],"paper,":[17],"we":[18,79],"present":[19],"hierarchical":[21],"framework":[22],"that":[23],"improves":[24],"sample-efficiency":[25,66],"and":[26,50,87,127,142],"generalizability":[27],"of":[28,40,67,75,114,132],"learned":[29],"locomotion":[30,42],"skills":[31],"real-world":[33],"robots.":[34],"Our":[35,120],"approach":[36,134],"divides":[37],"the":[38,130],"goal-oriented":[41],"into":[43],"two":[44,112],"sub-problems:":[45],"learning":[46,68],"diverse":[47],"primitives":[48,61],"skills,":[49],"using":[51],"model-based":[52],"planning":[53],"sequence":[55],"these":[56],"skills.":[57],"We":[58],"parametrize":[59],"our":[60,133],"as":[62],"cyclic":[63],"movements,":[64],"improving":[65],"from":[69,116],"scratch":[70,117],"18":[73],"degrees":[74],"freedom":[76],"robot.":[77],"Then,":[78],"learn":[80,100],"coarse":[81],"dynamics":[82],"models":[83],"over":[84],"primitive":[85],"cycles":[86],"use":[88],"them":[89],"in":[90,139],"model":[92],"predictive":[93],"control":[94],"framework.":[95],"This":[96],"allows":[97],"us":[98],"walk":[102],"up":[106],"12m":[108],"away,":[109],"after":[110],"about":[111],"hours":[113],"training":[115],"hardware.":[119],"results":[121],"Daisy":[124],"hexapod":[125],"simulation":[128],"demonstrate":[129],"efficacy":[131],"at":[135],"reaching":[136],"distant":[137],"targets,":[138],"different":[140],"environments,":[141],"with":[143],"sensory":[144],"noise.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}