{"id":"https://openalex.org/W4414165727","doi":"https://doi.org/10.1109/tcns.2025.3608070","title":"Distributed Sparse Bayesian Control Barrier Function and Its Application to Safe Persistent Exploration","display_name":"Distributed Sparse Bayesian Control Barrier Function and Its Application to Safe Persistent Exploration","publication_year":2025,"publication_date":"2025-09-09","ids":{"openalex":"https://openalex.org/W4414165727","doi":"https://doi.org/10.1109/tcns.2025.3608070"},"language":"en","primary_location":{"id":"doi:10.1109/tcns.2025.3608070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcns.2025.3608070","pdf_url":null,"source":{"id":"https://openalex.org/S2502544478","display_name":"IEEE Transactions on Control of Network Systems","issn_l":"2325-5870","issn":["2325-5870","2372-2533"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Control of Network Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057835766","display_name":"Kazuki Mizuta","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I46020346","display_name":"American Institute of Aeronautics and Astronautics","ror":"https://ror.org/00a1rzv11","country_code":"US","type":"other","lineage":["https://openalex.org/I46020346"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kazuki Mizuta","raw_affiliation_strings":["Department of Aeronautics and Astronautics, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Aeronautics and Astronautics, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I46020346","https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018425862","display_name":"Junya Yamauchi","orcid":"https://orcid.org/0000-0002-5827-486X"},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junya Yamauchi","raw_affiliation_strings":["Faculty of Engineering, University of Toyama, Toyama, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005851455","display_name":"Masayuki Fujita","orcid":"https://orcid.org/0000-0003-1772-0891"},"institutions":[{"id":"https://openalex.org/I125852741","display_name":"Kanazawa Institute of Technology","ror":"https://ror.org/02ws33e43","country_code":"JP","type":"education","lineage":["https://openalex.org/I125852741"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masayuki Fujita","raw_affiliation_strings":["Department of Robotics, Kanazawa Institute of Technology, Ishikawa, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Robotics, Kanazawa Institute of Technology, Ishikawa, Japan","institution_ids":["https://openalex.org/I125852741"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057835766"],"corresponding_institution_ids":["https://openalex.org/I201448701","https://openalex.org/I46020346"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30274299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"4","first_page":"3037","last_page":"3048"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9958999752998352,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9958999752998352,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9818000197410583,"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/T11801","display_name":"Reservoir Engineering and Simulation Methods","score":0.9678000211715698,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/scalability","display_name":"Scalability","score":0.612500011920929},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.438400000333786},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4262999892234802},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4162999987602234},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.3971000015735626},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.37720000743865967},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.35409998893737793},{"id":"https://openalex.org/keywords/decentralised-system","display_name":"Decentralised system","score":0.33799999952316284},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.336899995803833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6820999979972839},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.612500011920929},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.41780000925064087},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.3971000015735626},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.35409998893737793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3529999852180481},{"id":"https://openalex.org/C205875254","wikidata":"https://www.wikidata.org/wiki/Q17156857","display_name":"Decentralised system","level":3,"score":0.33799999952316284},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C132835097","wikidata":"https://www.wikidata.org/wiki/Q7663745","display_name":"System safety","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3059000074863434},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.29170000553131104},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2833999991416931},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.27070000767707825},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcns.2025.3608070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcns.2025.3608070","pdf_url":null,"source":{"id":"https://openalex.org/S2502544478","display_name":"IEEE Transactions on Control of Network Systems","issn_l":"2325-5870","issn":["2325-5870","2372-2533"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Control of Network Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1880805667","https://openalex.org/W1977189000","https://openalex.org/W2012807278","https://openalex.org/W2025291543","https://openalex.org/W2039245308","https://openalex.org/W2044454977","https://openalex.org/W2072931689","https://openalex.org/W2093287782","https://openalex.org/W2101709642","https://openalex.org/W2124435169","https://openalex.org/W2133844819","https://openalex.org/W2505781211","https://openalex.org/W2736865107","https://openalex.org/W2789773866","https://openalex.org/W2944445404","https://openalex.org/W2962807522","https://openalex.org/W2968945909","https://openalex.org/W2969721933","https://openalex.org/W2998553944","https://openalex.org/W3112335585","https://openalex.org/W3118888403","https://openalex.org/W3131411499","https://openalex.org/W3208077644","https://openalex.org/W4200492903","https://openalex.org/W4205504030","https://openalex.org/W4210985923","https://openalex.org/W4252189904","https://openalex.org/W4295832199","https://openalex.org/W4298876635","https://openalex.org/W4312307243","https://openalex.org/W4313591001"],"related_works":[],"abstract_inverted_index":{"Multi-robot":[0],"systems":[1],"offer":[2],"significant":[3],"advantages":[4],"for":[5],"autonomously":[6],"exploring":[7],"large-scale,":[8],"unknown":[9],"environments.":[10],"A":[11],"critical":[12],"challenge":[13],"in":[14,25],"these":[15,98],"applications,":[16],"however,":[17],"is":[18,69,116],"ensuring":[19],"the":[20,95,134],"safety":[21,62,113],"of":[22,66,133],"all":[23],"agents":[24],"a":[26,47,53,70,77,111,121],"scalable":[27],"and":[28,37,106,142],"efficient":[29],"manner,":[30],"especially":[31],"when":[32],"operating":[33],"with":[34,144],"decentralized":[35],"coordination":[36],"limited":[38],"communication.":[39],"To":[40,91],"overcome":[41],"this":[42,44,128],"limitation,":[43],"article":[45],"presents":[46],"fully":[48],"distributed":[49],"algorithm":[50,136],"that":[51],"enables":[52],"multi-robot":[54],"team":[55],"to":[56,86,109],"explore":[57],"cooperatively":[58],"while":[59],"maintaining":[60],"formal":[61],"guarantees.":[63],"The":[64,131],"core":[65],"our":[67],"approach":[68],"framework":[71],"where":[72],"each":[73],"robot":[74],"individually":[75],"trains":[76],"sparse":[78],"Bayesian":[79],"classifier":[80],"using":[81],"its":[82],"local":[83],"LiDAR":[84],"data":[85],"probabilistically":[87],"model":[88],"unsafe":[89],"regions.":[90],"achieve":[92],"collaborative":[93,129],"awareness,":[94],"robots":[96],"exchange":[97],"compact,":[99],"learned":[100],"models,":[101],"not":[102],"high-volume":[103],"raw":[104],"data,":[105],"fuse":[107],"them":[108],"construct":[110],"shared":[112],"map.":[114,130],"Safety":[115],"then":[117],"formally":[118],"guaranteed":[119],"through":[120,139],"control":[122],"barrier":[123],"function":[124],"(CBF)":[125],"derived":[126],"from":[127],"effectiveness":[132],"proposed":[135],"are":[137],"validated":[138],"both":[140],"simulations":[141],"experiments":[143],"physical":[145],"ground":[146],"robots.":[147]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
