{"id":"https://openalex.org/W4417282253","doi":"https://doi.org/10.1109/pimrc62392.2025.11275264","title":"Direct Policy Transfer Method for Multi-UAV Autonomous Navigation in Unknown Environment","display_name":"Direct Policy Transfer Method for Multi-UAV Autonomous Navigation in Unknown Environment","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4417282253","doi":"https://doi.org/10.1109/pimrc62392.2025.11275264"},"language":null,"primary_location":{"id":"doi:10.1109/pimrc62392.2025.11275264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc62392.2025.11275264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 36th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-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/A5015814760","display_name":"Dujia Yang","orcid":"https://orcid.org/0000-0002-9309-9067"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dujia Yang","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Engineering,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Engineering,Hefei,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437597","display_name":"Ao Zhang","orcid":"https://orcid.org/0000-0003-0386-1255"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ao Zhang","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Engineering,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Engineering,Hefei,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100632535","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-4593-5809"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Engineering,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Engineering,Hefei,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100387514","display_name":"Hui Liu","orcid":"https://orcid.org/0000-0001-7545-7986"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Liu","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Engineering,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Engineering,Hefei,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076565994","display_name":"Junan Yang","orcid":"https://orcid.org/0000-0002-9336-2152"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junan Yang","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Engineering,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Engineering,Hefei,China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35712664,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.7423999905586243,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.7423999905586243,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.047600001096725464,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11133","display_name":"UAV Applications and Optimization","score":0.040300000458955765,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/maxima-and-minima","display_name":"Maxima and minima","score":0.6031000018119812},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5843999981880188},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5615000128746033},{"id":"https://openalex.org/keywords/local-optimum","display_name":"Local optimum","score":0.5113000273704529},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.49219998717308044},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.49000000953674316},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.46470001339912415},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.42149999737739563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6299999952316284},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.6031000018119812},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5843999981880188},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5615000128746033},{"id":"https://openalex.org/C141934464","wikidata":"https://www.wikidata.org/wiki/Q3305386","display_name":"Local optimum","level":2,"score":0.5113000273704529},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.49219998717308044},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.46470001339912415},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.42149999737739563},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4147000014781952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41190001368522644},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3921000063419342},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.38989999890327454},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.3407999873161316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3319000005722046},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26910001039505005},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26350000500679016}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc62392.2025.11275264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc62392.2025.11275264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 36th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2177274602","https://openalex.org/W2752782242","https://openalex.org/W3154552588","https://openalex.org/W4322742245","https://openalex.org/W4381734765","https://openalex.org/W4385194665","https://openalex.org/W4387662490","https://openalex.org/W4392944997","https://openalex.org/W4394841726","https://openalex.org/W4403998770","https://openalex.org/W4404235483","https://openalex.org/W4405514980","https://openalex.org/W4406276444","https://openalex.org/W4407415438"],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"navigation":[1,156],"for":[2,11,160],"UAV":[3],"swarms":[4],"in":[5,112,134,154],"unknown":[6,124,162],"environments":[7],"holds":[8],"critical":[9],"importance":[10],"applications":[12],"ranging":[13],"from":[14,65],"disaster":[15],"response":[16],"to":[17,47,137,146],"military":[18],"reconnaissance,":[19],"yet":[20],"faces":[21],"multifaceted":[22],"challenges":[23],"including":[24],"dynamic":[25],"obstacle":[26],"avoidance,":[27],"real-time":[28],"computational":[29,158],"constraints,":[30],"and":[31,69,107,140,157],"absence":[32],"of":[33],"environmental":[34,62],"priors.":[35],"Conventional":[36],"path":[37],"planning":[38],"methods":[39],"(e.g.,":[40],"artificial":[41],"potential":[42],"fields,":[43],"APF)":[44],"frequently":[45],"succumb":[46],"local":[48,110],"optima":[49],"under":[50],"global":[51],"information":[52],"scarcity,":[53],"while":[54],"deep":[55],"reinforcement":[56],"learning":[57],"(DRL)":[58],"approaches,":[59],"despite":[60],"their":[61],"adaptability,":[63],"suffer":[64],"low":[66],"sample":[67],"efficiency":[68,89,159],"slow":[70],"convergence.":[71],"This":[72],"study":[73],"proposes":[74],"a":[75],"Direct":[76],"Policy":[77,81],"Transfer-enhanced":[78],"Multi-Agent":[79],"Proximal":[80],"Optimization":[82],"framework":[83,96],"(DPT-MAPPO),":[84],"merging":[85],"APF":[86,114,147],"spatial":[87],"modeling":[88],"with":[90],"DRL":[91],"adaptive":[92],"optimization.":[93],"Specially,":[94],"the":[95,128,150],"accelerates":[97],"environment-task":[98],"mapping":[99],"during":[100],"early":[101],"training":[102],"via":[103],"APF-guided":[104],"policy":[105],"priors":[106],"resolves":[108],"inherent":[109],"minima":[111],"conventional":[113],"through":[115],"DRL-driven":[116],"stochastic":[117],"exploration.":[118],"Experimental":[119],"validation":[120],"across":[121],"three":[122],"representative":[123],"scenarios":[125],"demonstrates":[126],"that":[127],"proposed":[129],"method":[130],"attained":[131],"4-fold":[132],"acceleration":[133],"convergence":[135],"compared":[136,145],"MAPPO":[138],"algorithms":[139],"16%":[141],"higher":[142],"success":[143],"rate":[144],"algorithms,":[148],"confirming":[149],"framework\u2019s":[151],"dual":[152],"advantages":[153],"safe":[155],"complex":[161],"environments.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-12T00:00:00"}