{"id":"https://openalex.org/W7164016209","doi":"https://doi.org/10.48550/arxiv.2606.09215","title":"MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation","display_name":"MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation","publication_year":2026,"publication_date":"2026-06-08","ids":{"openalex":"https://openalex.org/W7164016209","doi":"https://doi.org/10.48550/arxiv.2606.09215"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09215","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09215","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.09215","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138219942","display_name":"Jia Zheng (140297)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138203244","display_name":"Teli Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Teli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138281954","display_name":"Yudong Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Yudong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138260432","display_name":"Zifan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138234567","display_name":"Shuo Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Shuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138224315","display_name":"Junwei Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Junwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.6951000094413757,"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":0.6951000094413757,"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":0.06499999761581421,"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":0.04399999976158142,"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/torso","display_name":"Torso","score":0.6894999742507935},{"id":"https://openalex.org/keywords/humanoid-robot","display_name":"Humanoid robot","score":0.6804999709129333},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.645799994468689},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5576000213623047},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.4401000142097473},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.3422999978065491},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.3280999958515167}],"concepts":[{"id":"https://openalex.org/C523889960","wikidata":"https://www.wikidata.org/wiki/Q160695","display_name":"Torso","level":2,"score":0.6894999742507935},{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.6804999709129333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6579999923706055},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.645799994468689},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5576000213623047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.544700026512146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45329999923706055},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.4401000142097473},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3977999985218048},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.3422999978065491},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.31859999895095825},{"id":"https://openalex.org/C193081819","wikidata":"https://www.wikidata.org/wiki/Q4132092","display_name":"Video feedback","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.29319998621940613},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C2992583082","wikidata":"https://www.wikidata.org/wiki/Q9645","display_name":"Upper body","level":3,"score":0.260699987411499},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09215","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09215","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.09215","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09215","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5270377397537231,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"World":[0],"Action":[1],"Models":[2],"(WAMs)":[3],"couple":[4],"a":[5,46,56,83,92,106,116,139],"video":[6,107,150],"dynamics":[7,156],"prior":[8],"to":[9,77,153,158,214],"the":[10,40,52,75,98,101,112,149,159,181],"policy":[11,49,99],"and":[12,66,73,120,135,157,191],"have":[13],"shown":[14],"encouraging":[15],"results":[16,203],"on":[17,100,180],"tabletop":[18,212],"manipulation,":[19],"but":[20],"iterative":[21],"denoising":[22,103],"over":[23,185],"high-dimensional":[24],"video-action":[25],"latents":[26],"leaves":[27],"them":[28],"too":[29],"slow":[30],"for":[31],"real-time":[32,84],"humanoid":[33,89,161,218],"loco-manipulation.":[34],"The":[35],"problem":[36],"is":[37],"compounded":[38],"by":[39,96,184],"dominant":[41],"hierarchical":[42],"paradigm,":[43],"in":[44,69,138,171,187],"which":[45],"high-level":[47],"manipulation":[48,137,213],"controls":[50],"only":[51],"upper":[53,65],"body":[54,68],"while":[55],"low-level":[57],"controller":[58],"tracks":[59],"coarse":[60],"base":[61],"commands":[62],"--":[63],"placing":[64],"lower":[67],"inconsistent":[70],"action":[71,141],"spaces":[72],"reducing":[74],"legs":[76],"balance-preserving":[78],"locomotion.":[79],"We":[80],"present":[81],"MotionWAM,":[82],"WAM":[85],"that":[86,125,196,205],"drives":[87],"autonomous":[88],"loco-manipulation":[90],"from":[91,211],"single":[93,140],"egocentric":[94,154],"camera":[95],"conditioning":[97],"intermediate":[102],"features":[104],"of":[105],"world":[108,151],"model.":[109],"MotionWAM":[110,169],"replaces":[111],"upper-lower":[113,198],"split":[114],"with":[115],"unified":[117],"motion":[118,123],"latent":[119],"predicts":[121],"whole-body":[122,217],"tokens":[124],"jointly":[126],"cover":[127],"locomotion,":[128],"torso":[129],"motion,":[130],"height":[131],"regulation,":[132],"foot":[133,194],"interaction,":[134],"hand":[136],"space.":[142],"A":[143],"three-stage":[144],"learning":[145],"framework":[146],"progressively":[147],"adapts":[148],"model":[152],"visual":[155],"target":[160],"embodiment.":[162],"On":[163],"nine":[164],"real-world":[165],"Unitree":[166],"G1":[167],"tasks,":[168],"runs":[170],"real":[172],"time,":[173],"substantially":[174],"outperforms":[175],"Vision-Language-Action":[176],"(VLA)":[177],"baselines":[178],"fine-tuned":[179],"same":[182],"demonstrations":[183],"30%":[186],"overall":[188],"success":[189],"rate,":[190],"executes":[192],"task-driven":[193],"interaction":[195],"decoupled":[197],"policies":[199],"cannot":[200],"reach.":[201],"Our":[202],"suggest":[204],"video-pretrained":[206],"WAMs":[207],"can":[208],"be":[209],"lifted":[210],"coordinated,":[215],"human-like":[216],"control.":[219]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}
