{"id":"https://openalex.org/W4405735198","doi":"https://doi.org/10.1080/01691864.2024.2442718","title":"Footstep reward for energy-efficient quadruped gait generation and transition through deep reinforcement learning","display_name":"Footstep reward for energy-efficient quadruped gait generation and transition through deep reinforcement learning","publication_year":2024,"publication_date":"2024-12-24","ids":{"openalex":"https://openalex.org/W4405735198","doi":"https://doi.org/10.1080/01691864.2024.2442718"},"language":"en","primary_location":{"id":"doi:10.1080/01691864.2024.2442718","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01691864.2024.2442718","pdf_url":null,"source":{"id":"https://openalex.org/S192584203","display_name":"Advanced Robotics","issn_l":"0169-1864","issn":["0169-1864","1568-5535"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advanced Robotics","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/A5115624869","display_name":"Lucas Sulpice","orcid":null},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Lucas Sulpice","raw_affiliation_strings":["Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072945772","display_name":"Dai Owaki","orcid":"https://orcid.org/0000-0003-1217-3892"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Dai Owaki","raw_affiliation_strings":["Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060102825","display_name":"Mitsuhiro Hayashibe","orcid":"https://orcid.org/0000-0001-6179-5706"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Mitsuhiro Hayashibe","raw_affiliation_strings":["Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5060102825"],"corresponding_institution_ids":["https://openalex.org/I201537933"],"apc_list":null,"apc_paid":null,"fwci":1.0089,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72701336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"39","issue":"1","first_page":"71","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10879","display_name":"Robotic Locomotion and Control","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10879","display_name":"Robotic Locomotion and Control","score":0.9998000264167786,"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/T11023","display_name":"Prosthetics and Rehabilitation Robotics","score":0.9902999997138977,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9857000112533569,"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/gait","display_name":"Gait","score":0.8563002347946167},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.565253496170044},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5203216075897217},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.49348270893096924},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4749244153499603},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43328115344047546},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4103904962539673},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.38670870661735535},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2922363877296448},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.17227190732955933}],"concepts":[{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.8563002347946167},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.565253496170044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5203216075897217},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.49348270893096924},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4749244153499603},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43328115344047546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4103904962539673},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.38670870661735535},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2922363877296448},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.17227190732955933},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/01691864.2024.2442718","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01691864.2024.2442718","pdf_url":null,"source":{"id":"https://openalex.org/S192584203","display_name":"Advanced Robotics","issn_l":"0169-1864","issn":["0169-1864","1568-5535"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advanced Robotics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G4266316835","display_name":"\u904b\u52d5\u30b7\u30ca\u30b8\u30fc\u306b\u57fa\u3065\u304f\u6df1\u5c64\u5b66\u7fd2\u30d9\u30fc\u30b9\u904b\u52d5\u5236\u5fa1\u8a08\u7b97\u306e\u9ad8\u901f\u5316\u3068\u4f53\u7cfb\u5316","funder_award_id":"24K00841","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8471435614","display_name":"Environment Adaptation Mechanisms Decoded from Control of Insect-Peripersonal Space (i-PPS) Through Sensory, Motor, and Brain Interventions","funder_award_id":"23H00481","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1979210371","https://openalex.org/W1986105765","https://openalex.org/W2020255726","https://openalex.org/W2123520777","https://openalex.org/W2139053308","https://openalex.org/W2158782408","https://openalex.org/W2296073425","https://openalex.org/W2694031977","https://openalex.org/W2784449021","https://openalex.org/W2909331752","https://openalex.org/W2942905169","https://openalex.org/W2964056357","https://openalex.org/W3010768390","https://openalex.org/W3093922502","https://openalex.org/W3100789280","https://openalex.org/W3104876774","https://openalex.org/W3105609823","https://openalex.org/W3109424835","https://openalex.org/W3118984173","https://openalex.org/W3199990163","https://openalex.org/W4200453351","https://openalex.org/W4252907012","https://openalex.org/W4283069285","https://openalex.org/W4309323738","https://openalex.org/W4402216758"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W2024136090","https://openalex.org/W4391331176","https://openalex.org/W2031695474","https://openalex.org/W2586732548","https://openalex.org/W2964765435"],"abstract_inverted_index":{"The":[0],"generation":[1],"of":[2,98,129,141],"quadruped":[3,62],"robot":[4],"gait":[5,30,37,55,87,104,117,150,161],"through":[6],"deep":[7],"reinforcement":[8],"learning":[9,50],"(DRL)":[10],"has":[11],"emerged":[12],"as":[13,32,34],"a":[14,74],"prominent":[15],"topic":[16],"in":[17,25,35],"recent":[18],"years.":[19],"However,":[20],"DRL":[21,67,76],"methods":[22,40],"face":[23],"challenges":[24],"generating":[26,99],"specific":[27,86],"and":[28,57,102,135,148,163,177],"energy-efficient":[29],"patterns,":[31],"well":[33],"achieving":[36],"transition.":[38],"These":[39],"often":[41],"require":[42],"imposing":[43],"restrictions":[44],"on":[45,48],"movement":[46,64],"or":[47],"the":[49,61,127,155,166],"process":[51],"to":[52,83,115,125,159,170],"achieve":[53,165],"proper":[54],"specification":[56,118],"generation,":[58],"thereby":[59],"limiting":[60],"model":[63,133],"achievable":[65],"with":[66],"training.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72,121,153],"propose":[73],"new":[75],"reward":[77],"design":[78],"method,":[79],"called":[80],"FootStep":[81,156],"Reward,":[82],"successfully":[84,164],"generate":[85,160],"patterns":[88,105],"that":[89],"exhibit":[90],"animal-like":[91],"energetic":[92],"properties.":[93],"Our":[94],"method":[95,124,158],"is":[96],"capable":[97],"Walk,":[100,146],"Trot,":[101],"Gallop":[103,149],"at":[106,175],"any":[107],"velocity":[108],"while":[109],"demonstrating":[110],"better":[111],"energy":[112],"efficiency":[113],"compared":[114],"similar":[116],"methods.":[119],"Additionally,":[120],"employ":[122],"our":[123,139],"analyze":[126],"impact":[128],"two":[130],"body":[131],"parameters:":[132],"mass":[134],"joint":[136],"stiffness,":[137],"increasing":[138],"understanding":[140],"how":[142],"these":[143],"parameters":[144],"influence":[145],"Trot":[147,171],"efficiency.":[151],"Finally,":[152],"implement":[154],"Reward":[157],"transitions":[162],"transition":[167],"from":[168],"Walk":[169],"gait,":[172],"optimizing":[173],"locomotion":[174],"low":[176],"medium":[178],"velocities.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":4}],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2025-10-10T00:00:00"}
