{"id":"https://openalex.org/W7164900159","doi":"https://doi.org/10.48550/arxiv.2606.14882","title":"DynaHMRC: Decentralized Heterogeneous Multi-Robot Collaboration for Dynamic Tasks with Large Language Models","display_name":"DynaHMRC: Decentralized Heterogeneous Multi-Robot Collaboration for Dynamic Tasks with Large Language Models","publication_year":2026,"publication_date":"2026-06-12","ids":{"openalex":"https://openalex.org/W7164900159","doi":"https://doi.org/10.48550/arxiv.2606.14882"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.14882","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14882","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.2606.14882","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138711858","display_name":"Wenhao Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Wenhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071790882","display_name":"Yuang Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yu'ang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138757318","display_name":"Yifan Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duan, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102735864","display_name":"Jie Peng","orcid":"https://orcid.org/0000-0002-6957-3881"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085274223","display_name":"Guanting Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Guanting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122304301","display_name":"Ka-Veng Yuen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuen, Ka-Veng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138690946","display_name":"Yanyong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yanyong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138691580","display_name":"Jianmin Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Jianmin","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":0.26019999384880066,"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":0.26019999384880066,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.07760000228881836,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10028","display_name":"Topic Modeling","score":0.07029999792575836,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/bottleneck","display_name":"Bottleneck","score":0.7562000155448914},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.6428999900817871},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6140999794006348},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5648999810218811},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5392000079154968},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5188999772071838},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45890000462532043},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.43560001254081726}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7562000155448914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753000020980835},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.6428999900817871},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6140999794006348},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5648999810218811},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5188999772071838},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45890000462532043},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4465000033378601},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.43560001254081726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4341000020503998},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.39320001006126404},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.38850000500679016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3840999901294708},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2854999899864197},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C2780021488","wikidata":"https://www.wikidata.org/wiki/Q759682","display_name":"Task management","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.2533999979496002},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.14882","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14882","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.2606.14882","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14882","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,89],"(LLMs)":[3],"provide":[4],"robots":[5],"with":[6,140,209],"richer":[7],"task":[8,60,71,138,160,173],"understanding":[9],"and":[10,39,51,121,145,165,190,212],"adaptability,":[11],"making":[12,86],"them":[13],"promising":[14,217],"for":[15,75,91],"coordinating":[16],"heterogeneous":[17,126],"multi-robot":[18],"systems":[19],"in":[20,104],"long-horizon":[21],"tasks.":[22,93],"Despite":[23],"this":[24],"potential,":[25],"several":[26],"challenges":[27],"remain":[28],"underexplored:":[29],"(1)":[30],"Centralized":[31],"LLM":[32,112],"schedulers":[33],"scale":[34],"poorly":[35],"as":[36,109,132,220],"team":[37,127,167,221],"size":[38,222],"environmental":[40],"complexity":[41],"increase.":[42],"A":[43],"single":[44],"model":[45],"must":[46],"process":[47],"excessive":[48],"contextual":[49],"information,":[50],"long-context":[52],"approximation":[53],"may":[54],"degrade":[55],"reasoning":[56],"quality;":[57],"(2)":[58],"Existing":[59],"formulations":[61],"insufficiently":[62],"consider":[63],"dynamic":[64,163,172],"settings,":[65],"while":[66,215],"robust":[67],"adaptation":[68],"to":[69,169,182,194],"evolving":[70],"conditions":[72],"is":[73],"essential":[74],"real-world":[76],"deployment;":[77],"(3)":[78],"Domain-specific":[79],"data":[80],"scarcity":[81],"limits":[82],"specialized":[83,196],"robotic":[84],"reasoning,":[85],"proprietary":[87],"general-purpose":[88],"inefficient":[90],"expert":[92,188],"To":[94],"address":[95],"these":[96],"limitations,":[97],"we":[98,177],"propose":[99],"DynaHMRC,":[100],"a":[101,110,133,156],"decentralized":[102],"framework":[103],"which":[105],"each":[106],"robot":[107,151],"acts":[108],"role-aware":[111],"agent.":[113],"This":[114],"design":[115],"mitigates":[116],"the":[117,184,225],"single-model":[118],"context":[119],"bottleneck":[120],"supports":[122],"flexible":[123],"collaboration":[124,131],"across":[125],"configurations.":[128],"DynaHMRC":[129,201],"organizes":[130],"four-stage":[134],"closed-loop":[135],"process:":[136],"self-description,":[137],"allocation":[139],"leadership":[141],"bidding,":[142],"leader":[143],"election,":[144],"reflective":[146],"execution,":[147],"supported":[148],"by":[149],"executable":[150],"interfaces.":[152],"We":[153],"further":[154],"develop":[155],"benchmark":[157],"covering":[158],"three":[159],"families,":[161],"four":[162],"variations,":[164],"six":[166],"configurations":[168],"systematically":[170],"study":[171],"modeling.":[174],"In":[175],"addition,":[176],"conduct":[178],"an":[179],"empirical":[180],"analysis":[181],"guide":[183],"construction":[185],"of":[186],"domain-specific":[187],"datasets":[189],"fine-tune":[191],"pretrained":[192],"LLMs":[193],"improve":[195],"competence.":[197],"Experiments":[198],"show":[199],"that":[200],"achieves":[202],"higher":[203],"success":[204],"rates":[205],"than":[206],"strong":[207],"baselines":[208],"fewer":[210],"action":[211],"communication":[213],"steps,":[214],"demonstrating":[216],"scalability":[218],"trends":[219],"grows":[223],"within":[224],"evaluated":[226],"settings.":[227]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-17T00:00:00"}
