{"id":"https://openalex.org/W7134909062","doi":"https://doi.org/10.48550/arxiv.2603.09574","title":"SCDP: Learning Humanoid Locomotion from Partial Observations via Mixed-Observation Distillation","display_name":"SCDP: Learning Humanoid Locomotion from Partial Observations via Mixed-Observation Distillation","publication_year":2026,"publication_date":"2026-03-10","ids":{"openalex":"https://openalex.org/W7134909062","doi":"https://doi.org/10.48550/arxiv.2603.09574"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.09574","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09574","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.09574","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075832805","display_name":"Milo Carroll","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carroll, Milo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109710738","display_name":"Tianhu Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Tianhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128759231","display_name":"Lingfan Bao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bao, Lingfan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128776823","display_name":"Chengxu Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Chengxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128718772","display_name":"Zhibin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhibin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T10879","display_name":"Robotic Locomotion and Control","score":0.4805000126361847,"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":0.4805000126361847,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.10109999775886536,"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/T12290","display_name":"Human Motion and Animation","score":0.09350000321865082,"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/humanoid-robot","display_name":"Humanoid robot","score":0.8064000010490417},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6283000111579895},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5131999850273132},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4812000095844269},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4767000079154968},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4268999993801117},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4034999907016754},{"id":"https://openalex.org/keywords/motion-control","display_name":"Motion control","score":0.36489999294281006}],"concepts":[{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.8064000010490417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6650999784469604},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6283000111579895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5400999784469604},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5131999850273132},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4812000095844269},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4767000079154968},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4268999993801117},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4034999907016754},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3698999881744385},{"id":"https://openalex.org/C145565327","wikidata":"https://www.wikidata.org/wiki/Q852514","display_name":"Motion control","level":3,"score":0.36489999294281006},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.361299991607666},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.34529998898506165},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3228999972343445},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.28349998593330383},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26190000772476196},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2597000002861023},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2538999915122986},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.09574","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09574","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.09574","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09574","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Distilling":[0],"humanoid":[1,37,158],"locomotion":[2,38,114,166],"control":[3,128],"from":[4,53],"offline":[5],"datasets":[6],"into":[7],"deployable":[8],"policies":[9],"remains":[10],"a":[11,155],"challenge,":[12],"as":[13],"existing":[14],"methods":[15],"rely":[16],"on":[17,61,112,126,154],"privileged":[18,69,141],"full-body":[19],"states":[20],"that":[21,35],"require":[22],"complex":[23],"and":[24,92,104,115,130],"often":[25],"unreliable":[26],"state":[27,48,99,171],"estimation.":[28,49,172],"We":[29,84,109],"present":[30],"Sensor-Conditioned":[31],"Diffusion":[32],"Policies":[33],"(SCDP)":[34],"enables":[36],"using":[39,144],"only":[40,145],"onboard":[41,146],"sensors,":[42],"eliminating":[43],"the":[44,74,78,102,151],"need":[45],"for":[46],"explicit":[47],"SCDP":[50,111,122],"decouples":[51],"sensing":[52,169],"supervision":[54],"through":[55],"mixed-observation":[56],"training:":[57],"diffusion":[58],"model":[59,75,103],"conditions":[60],"sensor":[62],"histories":[63],"while":[64,143],"being":[65],"supervised":[66],"to":[67,76,96,105,140],"predict":[68],"future":[70],"state-action":[71],"trajectories,":[72],"enforcing":[73],"infer":[77],"motion":[79,116],"dynamics":[80],"under":[81],"partial":[82],"observability.":[83],"further":[85],"develop":[86],"restricted":[87],"denoising,":[88],"context":[89],"distribution":[90],"alignment,":[91],"context-aware":[93],"attention":[94],"masking":[95],"encourage":[97],"implicit":[98],"estimation":[100],"within":[101],"prevent":[106],"train-deploy":[107],"mismatch.":[108],"validate":[110],"velocity-commanded":[113],"reference":[117],"tracking":[118,132],"tasks.":[119],"In":[120],"simulation,":[121],"achieves":[123],"near-perfect":[124],"success":[125,133],"velocity":[127],"(99-100%)":[129],"93%":[131],"in":[134],"AMASS":[135],"test":[136],"set,":[137],"performing":[138],"comparable":[139],"baselines":[142],"sensors.":[147],"Finally,":[148],"we":[149],"deploy":[150],"trained":[152],"policy":[153],"real":[156,164],"G1":[157],"at":[159],"50":[160],"Hz,":[161],"demonstrating":[162],"robust":[163],"robot":[165],"without":[167],"external":[168],"or":[170]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-12T00:00:00"}
