{"id":"https://openalex.org/W7155195000","doi":"https://doi.org/10.48550/arxiv.2604.19670","title":"Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming","display_name":"Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming","publication_year":2026,"publication_date":"2026-04-21","ids":{"openalex":"https://openalex.org/W7155195000","doi":"https://doi.org/10.48550/arxiv.2604.19670"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2604.19670","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.19670","pdf_url":"https://arxiv.org/pdf/2604.19670","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2604.19670","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068310224","display_name":"Alex Cuellar","orcid":"https://orcid.org/0009-0006-3866-2335","observed_orcids":["https://orcid.org/0009-0006-3866-2335"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cuellar, Alex","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052368316","display_name":"Michael Hagenow","orcid":"https://orcid.org/0000-0002-4532-2949","observed_orcids":["https://orcid.org/0000-0002-4532-2949"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hagenow, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5044369720","display_name":"Julie Shah","orcid":"https://orcid.org/0000-0003-1338-8107","observed_orcids":["https://orcid.org/0000-0003-1338-8107"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shah, Julie","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":true,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9678000211715698,"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":0.9678000211715698,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.012600000016391277,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.002400000113993883,"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/human-robot-teaming","display_name":"human-robot teams","score":0.9860000014305115},{"id":"https://openalex.org/keywords/task-scheduling","display_name":"task scheduling","score":0.7210000157356262},{"id":"https://openalex.org/keywords/motion-planning","display_name":"motion planning","score":0.46399998664855957},{"id":"https://openalex.org/keywords/diffusion-models","display_name":"diffusion models","score":0.7689999938011169},{"id":"https://openalex.org/keywords/spatial-interference","display_name":"spatial interference","score":0.6349999904632568},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"collision avoidance","score":0.8080000281333923},{"id":"https://openalex.org/keywords/robot-manipulators","display_name":"robot manipulators","score":0.37400001287460327},{"id":"https://openalex.org/keywords/user-study","display_name":"user study","score":0.492000013589859}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6958000063896179},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6276999711990356},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5490000247955322},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5282999873161316},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5151000022888184},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.4964999854564667},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.4779999852180481},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4607999920845032},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.45350000262260437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43689998984336853},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4106999933719635},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.29809999465942383},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.28760001063346863},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.28519999980926514},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2808000147342682},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.27090001106262207},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.26930001378059387},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2776544517","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Unexpected events","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2604.19670","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.19670","pdf_url":"https://arxiv.org/pdf/2604.19670","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2604.19670","doi":"https://doi.org/10.48550/arxiv.2604.19670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19670","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"pmh:oai:arXiv.org:2604.19670","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.19670","pdf_url":"https://arxiv.org/pdf/2604.19670","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Quality education","id":"https://metadata.un.org/sdg/4","score":0.5869090557098389}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7155195000.pdf","grobid_xml":"https://content.openalex.org/works/W7155195000.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Effective":[0],"human-robot":[1,17],"teaming":[2],"is":[3],"crucial":[4],"for":[5,142],"the":[6,24,38,89,148],"practical":[7],"deployment":[8],"of":[9,26,41,132,150],"robots":[10],"in":[11,64,77,158],"human":[12,29],"workspaces.":[13],"However,":[14],"optimizing":[15],"joint":[16],"plans":[18,52],"remains":[19],"a":[20,97,161,166,173],"challenge":[21],"due":[22],"to":[23,45,116,135,182],"difficulty":[25],"modeling":[27,104],"individualized":[28,144],"capabilities":[30],"and":[31,50,61,70,111,128,138,160,192,194,199],"preferences.":[32],"While":[33],"prior":[34],"research":[35],"has":[36],"leveraged":[37],"multi-cycle":[39],"structure":[40],"domains":[42],"like":[43],"manufacturing":[44],"learn":[46],"an":[47,105,155],"individual's":[48,106],"tendencies":[49],"adapt":[51],"over":[53,119],"repeated":[54],"interactions,":[55],"these":[56,101,143],"techniques":[57],"typically":[58],"consider":[59],"task-level":[60],"motion-level":[62,81],"adaptation":[63,153],"isolation.":[65],"Task-level":[66],"methods":[67,82],"optimize":[68],"allocation":[69],"scheduling":[71],"but":[72],"often":[73],"ignore":[74],"spatial":[75,107],"interference":[76],"close-proximity":[78],"scenarios;":[79],"conversely,":[80],"focus":[83],"on":[84],"collision":[85],"avoidance":[86],"while":[87],"ignoring":[88],"broader":[90],"task":[91,126],"context.":[92],"This":[93],"paper":[94],"introduces":[95],"RAPIDDS,":[96],"framework":[98],"that":[99],"unifies":[100],"approaches":[102],"by":[103],"behavior":[108,113],"(motion":[109],"paths)":[110],"temporal":[112],"(time":[114],"required":[115],"complete":[117],"tasks)":[118],"multiple":[120],"cycles.":[121],"RAPIDDS":[122],"then":[123],"jointly":[124],"adapts":[125],"schedules":[127],"steers":[129],"diffusion":[130],"models":[131],"robot":[133,163,168],"motions":[134],"maximize":[136],"efficiency":[137,191],"minimize":[139],"proximity":[140],"accounting":[141],"models.":[145],"We":[146],"demonstrate":[147],"importance":[149],"this":[151,203],"dual":[152],"through":[154],"ablation":[156],"study":[157,175],"simulation":[159],"physical":[162],"scenario":[164],"using":[165],"7-DOF":[167],"arm.":[169],"Finally,":[170],"we":[171],"present":[172],"user":[174,200],"(n=32)":[176],"showing":[177],"significant":[178],"plan":[179],"improvement":[180],"compared":[181],"non-adaptive":[183],"systems":[184],"across":[185],"both":[186],"objective":[187],"metrics,":[188],"such":[189],"as":[190],"proximity,":[193],"subjective":[195],"measures,":[196],"including":[197],"fluency":[198],"preference.":[201],"See":[202],"paper's":[204],"companion":[205],"video":[206],"at:":[207],"https://youtu.be/55Q3lq1fINs.":[208]},"counts_by_year":[],"updated_date":"2026-10-13T10:08:12.033832","created_date":"2026-04-23T00:00:00"}
