{"id":"https://openalex.org/W7124865633","doi":"https://doi.org/10.1109/access.2026.3655347","title":"Deep Reinforcement Learning-Based Pursuit\u2013Evasion Strategy for USVs in Complex Multi-Obstacle Environments","display_name":"Deep Reinforcement Learning-Based Pursuit\u2013Evasion Strategy for USVs in Complex Multi-Obstacle Environments","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7124865633","doi":"https://doi.org/10.1109/access.2026.3655347"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3655347","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655347","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3655347","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123415045","display_name":"Jian Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Liu","raw_affiliation_strings":["Naval Submarine Academy, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Naval Submarine Academy, Qingdao, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083692010","display_name":"Xing Shen","orcid":"https://orcid.org/0000-0001-5002-3030"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Shen","raw_affiliation_strings":["School of Mathematics and Statistics, Qingdao University, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Qingdao University, Qingdao, China","institution_ids":["https://openalex.org/I108688024"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hongwei Gao","orcid":"https://orcid.org/0000-0003-2243-4136"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Gao","raw_affiliation_strings":["School of Mathematics and Statistics, Qingdao University, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0003-2243-4136","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Qingdao University, Qingdao, China","institution_ids":["https://openalex.org/I108688024"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":28.1691,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97978194,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"14","issue":null,"first_page":"9917","last_page":"9934"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12158","display_name":"Guidance and Control Systems","score":0.881600022315979,"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"}},"topics":[{"id":"https://openalex.org/T12158","display_name":"Guidance and Control Systems","score":0.881600022315979,"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/T11082","display_name":"Spacecraft Dynamics and Control","score":0.029200000688433647,"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/T11622","display_name":"Maritime Navigation and Safety","score":0.013199999928474426,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7986999750137329},{"id":"https://openalex.org/keywords/observability","display_name":"Observability","score":0.7504000067710876},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6434000134468079},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5684000253677368},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5536999702453613},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.49399998784065247},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4629000127315521},{"id":"https://openalex.org/keywords/pursuer","display_name":"Pursuer","score":0.38269999623298645},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.37950000166893005}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7986999750137329},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.755299985408783},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.7504000067710876},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6434000134468079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6061000227928162},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5684000253677368},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5536999702453613},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4629000127315521},{"id":"https://openalex.org/C2776927521","wikidata":"https://www.wikidata.org/wiki/Q468489","display_name":"Pursuer","level":2,"score":0.38269999623298645},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C2776937971","wikidata":"https://www.wikidata.org/wiki/Q4384217","display_name":"Heading (navigation)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3655347","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655347","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3655347","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655347","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8169454336166382,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G1656196761","display_name":null,"funder_award_id":"XT2024301","funder_id":"https://openalex.org/F4320329228","funder_display_name":"Science Research Foundation of Xijing University"},{"id":"https://openalex.org/G5917278180","display_name":null,"funder_award_id":"72171126","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8844804342","display_name":null,"funder_award_id":"No. 72171126","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329228","display_name":"Science Research Foundation of Xijing University","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2766096873","https://openalex.org/W2904455790","https://openalex.org/W2911308106","https://openalex.org/W3035829937","https://openalex.org/W3046106022","https://openalex.org/W3156295478","https://openalex.org/W4213246061","https://openalex.org/W4220747123","https://openalex.org/W4312440760","https://openalex.org/W4321763414","https://openalex.org/W4386615302","https://openalex.org/W4399387796","https://openalex.org/W4405933903","https://openalex.org/W4416366456"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,96,110,118,127,148,152,170],"widespread":[2],"application":[3],"of":[4,155],"Unmanned":[5],"Surface":[6],"Vehicles":[7],"(USVs)":[8],"in":[9,17,44,62,85,134,158,192],"marine":[10],"monitoring":[11],"and":[12,19,42,58,105,120,144,181,200],"military":[13],"reconnaissance,":[14],"collaborative":[15,46],"pursuit":[16],"complex":[18],"dynamic":[20,40,141],"environments":[21],"faces":[22],"significant":[23],"challenges.":[24],"Traditional":[25],"path":[26],"planning":[27],"methods":[28],"(e.g.,":[29],"A*":[30],"algorithm,":[31],"artificial":[32],"potential":[33],"field)":[34],"suffer":[35],"from":[36],"limited":[37],"adaptability":[38],"to":[39,115,129,137],"obstacles":[41],"difficulty":[43],"multi-objective":[45],"optimization,":[47],"while":[48,125],"existing":[49],"deep":[50,75],"reinforcement":[51,76],"learning":[52,77,98],"approaches":[53],"often":[54],"neglect":[55],"partial":[56,83,204],"observability":[57],"variable-dimensional":[59],"observations,":[60],"resulting":[61],"insufficient":[63],"strategy":[64],"generalization.":[65],"To":[66],"address":[67],"these":[68],"challenges,":[69],"this":[70],"paper":[71],"proposes":[72],"a":[73,106],"POSG-based":[74],"framework":[78,111,172],"for":[79],"multi-USV":[80],"pursuit-evasion":[81],"under":[82,203],"observability,":[84],"which":[86],"an":[87,183],"enhanced":[88],"Multi-Agent":[89],"Soft":[90],"Actor-Critic":[91],"(MASAC)":[92],"algorithm":[93],"serves":[94],"as":[95],"core":[97],"component.":[99],"By":[100],"constructing":[101],"hybrid":[102],"observation":[103],"spaces":[104],"hierarchical":[107],"reward":[108],"function,":[109],"guides":[112],"pursuer":[113],"USVs":[114],"efficiently":[116],"approach":[117],"target":[119],"form":[121],"stable":[122,174],"encirclement":[123],"formations,":[124],"forcing":[126],"evader":[128],"adjust":[130],"its":[131],"escape":[132],"trajectory":[133],"real":[135],"time":[136],"delay":[138],"capture.":[139],"Through":[140],"feature-compression":[142],"encoding":[143],"obstacle-interaction":[145],"pattern":[146],"modeling,":[147],"proposed":[149,171],"method":[150],"alleviates":[151],"generalization":[153,202],"challenge":[154],"policy":[156],"networks":[157],"partially":[159],"observable":[160],"scenarios":[161],"with":[162],"varying":[163],"input":[164],"dimensions.":[165],"Experimental":[166],"results":[167],"show":[168],"that":[169],"reaches":[173],"convergence":[175],"after":[176],"approximately":[177],"3000":[178],"training":[179],"episodes":[180,191],"achieves":[182],"85%":[184],"capture":[185,198],"success":[186],"rate":[187],"over":[188],"100":[189],"evaluation":[190],"unseen":[193],"multi-obstacle":[194],"maps,":[195],"indicating":[196],"improved":[197],"efficiency":[199],"strong":[201],"observability.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2026-01-21T00:00:00"}