{"id":"https://openalex.org/W7129444799","doi":"https://doi.org/10.1109/mra.2026.3651673","title":"Cross-Embodiment Imitation: Learning a Unified Latent Space for Multirobot Control","display_name":"Cross-Embodiment Imitation: Learning a Unified Latent Space for Multirobot Control","publication_year":2026,"publication_date":"2026-02-17","ids":{"openalex":"https://openalex.org/W7129444799","doi":"https://doi.org/10.1109/mra.2026.3651673"},"language":null,"primary_location":{"id":"doi:10.1109/mra.2026.3651673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mra.2026.3651673","pdf_url":null,"source":{"id":"https://openalex.org/S132261465","display_name":"IEEE Robotics & Automation Magazine","issn_l":"1070-9932","issn":["1070-9932","1558-223X"],"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 & Automation Magazine","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/A5113085979","display_name":"Yashuai Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Yashuai Yan","raw_affiliation_strings":["Autonomous Systems Lab, TU Wien, Vienna, Austria"],"raw_orcid":"https://orcid.org/0009-0005-5489-6273","affiliations":[{"raw_affiliation_string":"Autonomous Systems Lab, TU Wien, Vienna, Austria","institution_ids":["https://openalex.org/I145847075"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121492402","display_name":"Dongheui Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Dongheui Lee","raw_affiliation_strings":["Autonomous Systems Lab, TU Wien, Vienna, Austria"],"raw_orcid":"https://orcid.org/0000-0003-1897-7664","affiliations":[{"raw_affiliation_string":"Autonomous Systems Lab, TU Wien, Vienna, Austria","institution_ids":["https://openalex.org/I145847075"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145847075"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1614355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"1","first_page":"167","last_page":"179"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.352400004863739,"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":0.352400004863739,"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":0.18209999799728394,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.11400000005960464,"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":0.8159999847412109},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7940000295639038},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5393999814987183},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5145000219345093},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4966999888420105},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.460099995136261},{"id":"https://openalex.org/keywords/retargeting","display_name":"Retargeting","score":0.44940000772476196},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.43149998784065247},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.421999990940094}],"concepts":[{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.8159999847412109},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7940000295639038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6927000284194946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6538000106811523},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5393999814987183},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5145000219345093},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C2780575108","wikidata":"https://www.wikidata.org/wiki/Q7316652","display_name":"Retargeting","level":2,"score":0.44940000772476196},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.43149998784065247},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41830000281333923},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3978999853134155},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3946000039577484},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C145565327","wikidata":"https://www.wikidata.org/wiki/Q852514","display_name":"Motion control","level":3,"score":0.3749000132083893},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.37380000948905945},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.3319000005722046},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31450000405311584},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C65401140","wikidata":"https://www.wikidata.org/wiki/Q7353385","display_name":"Robot control","level":4,"score":0.3018999993801117},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.28459998965263367},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C2779038628","wikidata":"https://www.wikidata.org/wiki/Q7248497","display_name":"Programming by demonstration","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mra.2026.3651673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mra.2026.3651673","pdf_url":null,"source":{"id":"https://openalex.org/S132261465","display_name":"IEEE Robotics & Automation Magazine","issn_l":"1070-9932","issn":["1070-9932","1558-223X"],"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 & Automation Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,128],"present":[1],"a":[2,12,41,96,110,161,193],"scalable":[3],"framework":[4],"for":[5,87],"cross-embodiment":[6],"humanoid":[7,23,30,197],"robot":[8,190],"control":[9,98,191],"by":[10,124,158],"learning":[11,159],"shared":[13],"latent":[14,43,103,120,156,168],"representation":[15],"that":[16,45,79,130,182],"unifies":[17],"motion":[18,48,61],"across":[19,50,64,192],"humans":[20],"and":[21,28,59,83,188],"diverse":[22,67],"platforms,":[24],"including":[25],"single-arm,":[26],"dual-arm,":[27],"legged":[29],"robots.":[31,178],"Our":[32],"method":[33,146],"proceeds":[34],"in":[35],"two":[36],"stages.":[37],"First,":[38],"we":[39,74,94],"construct":[40],"decoupled":[42],"space":[44,104,121,157],"captures":[46],"localized":[47],"patterns":[49],"different":[51],"body":[52],"parts":[53],"using":[54,105],"contrastive":[55],"learning,":[56],"enabling":[57],"accurate":[58],"flexible":[60],"retargeting":[62],"even":[63],"robots":[65,140,153],"with":[66],"morphologies.":[68],"To":[69],"enhance":[70],"alignment":[71],"among":[72],"embodiments,":[73],"introduce":[75],"tailored":[76],"similarity":[77],"metrics":[78],"combine":[80],"joint":[81],"rotation":[82],"end-effector":[84],"(EE)":[85],"positioning":[86],"critical":[88],"segments,":[89],"such":[90],"as":[91],"arms.":[92],"Then,":[93],"train":[95],"goal-conditioned":[97],"policy":[99,116,133],"directly":[100,136,173],"within":[101],"this":[102],"only":[106,160],"human":[107],"data.":[108],"Leveraging":[109],"conditional":[111],"variational":[112],"autoencoder":[113],"(c-VAE),":[114],"our":[115,145,183],"learns":[117],"to":[118,154,175],"predict":[119],"displacements":[122],"guided":[123],"intended":[125],"goal":[126],"directions.":[127],"show":[129],"the":[131,148,155,176],"trained":[132],"can":[134,170],"be":[135,172],"deployed":[137],"on":[138],"multiple":[139],"without":[141],"any":[142],"adaptation.":[143],"Furthermore,":[144],"supports":[147],"efficient":[149],"addition":[150],"of":[151,196],"new":[152,177],"lightweight":[162],"robot-specific":[163],"embedding":[164],"layer.":[165],"The":[166],"learned":[167],"policies":[169],"also":[171],"applied":[174],"Experimental":[179],"results":[180],"demonstrate":[181],"approach":[184],"enables":[185],"robust,":[186],"scalable,":[187],"embodiment-agnostic":[189],"wide":[194],"range":[195],"platforms.":[198]},"counts_by_year":[],"updated_date":"2026-03-26T06:05:38.182114","created_date":"2026-02-18T00:00:00"}