{"id":"https://openalex.org/W7154026618","doi":"https://doi.org/10.48550/arxiv.2604.08664","title":"Generative Simulation for Policy Learning in Physical Human-Robot Interaction","display_name":"Generative Simulation for Policy Learning in Physical Human-Robot Interaction","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7154026618","doi":"https://doi.org/10.48550/arxiv.2604.08664"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.08664","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08664","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":null,"license_id":null,"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.2604.08664","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133540067","display_name":"Junxiang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Junxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133529881","display_name":"Xinwen Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xinwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103214075","display_name":"Tiancheng Wu","orcid":"https://orcid.org/0009-0004-4850-0896"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Tiancheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133497776","display_name":"Julian Millan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Millan, Julian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133510629","display_name":"Nir Pechuk","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pechuk, Nir","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5075365855","display_name":"Zackory Erickson","orcid":"https://orcid.org/0000-0002-6760-6213"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erickson, Zackory","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.3149999976158142,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.3149999976158142,"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":0.28369998931884766,"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":0.1501999944448471,"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/pipeline","display_name":"Pipeline (software)","score":0.5975000262260437},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5940999984741211},{"id":"https://openalex.org/keywords/human\u2013robot-interaction","display_name":"Human\u2013robot interaction","score":0.5527999997138977},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5069000124931335},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.430400013923645},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.42719998955726624},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.4212000072002411},{"id":"https://openalex.org/keywords/policy-learning","display_name":"Policy learning","score":0.4162999987602234}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7107999920845032},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5975000262260437},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5971999764442444},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5940999984741211},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.5527999997138977},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4693000018596649},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.42719998955726624},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3402999937534332},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.32109999656677246},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29109999537467957},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26750001311302185}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.08664","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08664","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.08664","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08664","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Developing":[0],"autonomous":[1],"physical":[2],"human-robot":[3],"interaction":[4],"(pHRI)":[5],"systems":[6],"is":[7],"limited":[8],"by":[9],"the":[10,132],"scarcity":[11],"of":[12],"large-scale":[13,77],"training":[14],"data":[15,144],"to":[16,74,125],"learn":[17],"robust":[18],"robot":[19,64],"behaviors":[20],"for":[21,67,137],"real-world":[22],"applications.":[23],"In":[24],"this":[25,72],"paper,":[26],"we":[27,130],"introduce":[28,131],"a":[29,98],"zero-shot":[30,114],"\"text2sim2real\"":[31],"generative":[32,134],"simulation":[33,135,141],"framework":[34,73],"that":[35],"automatically":[36],"synthesizes":[37],"diverse":[38],"pHRI":[39,138],"scenarios":[40],"from":[41],"high-level":[42],"natural-language":[43],"prompts.":[44],"Leveraging":[45],"Large":[46],"Language":[47],"Models":[48,52],"(LLMs)":[49],"and":[50,63,81,107,122,146],"Vision-Language":[51],"(VLMs),":[53],"our":[54,95,155],"pipeline":[55,136],"procedurally":[56],"generates":[57],"soft-body":[58],"human":[59,127],"models,":[60],"scene":[61],"layouts,":[62],"motion":[65],"trajectories":[66],"assistive":[68,104],"tasks.":[69],"We":[70,93],"utilize":[71],"autonomously":[75],"collect":[76],"synthetic":[78],"demonstration":[79],"datasets":[80],"then":[82],"train":[83],"vision-based":[84],"imitation":[85],"learning":[86],"policies":[87,111],"operating":[88],"on":[89,101,154],"segmented":[90],"point":[91],"clouds.":[92],"evaluate":[94],"approach":[96],"through":[97],"user":[99],"study":[100],"two":[102],"physically":[103],"tasks:":[105],"scratching":[106],"bathing.":[108],"Our":[109],"learned":[110],"successfully":[112],"achieve":[113],"sim-to-real":[115],"transfer,":[116],"attaining":[117],"success":[118],"rates":[119],"exceeding":[120],"80%":[121],"demonstrating":[123],"resilience":[124],"unscripted":[126],"motion.":[128],"Overall,":[129],"first":[133],"applications,":[139],"automating":[140],"environment":[142],"synthesis,":[143],"collection,":[145],"policy":[147],"learning.":[148],"Additional":[149],"information":[150],"may":[151],"be":[152],"found":[153],"project":[156],"website:":[157],"https://rchi-lab.github.io/gen_phri/":[158]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-14T00:00:00"}
