{"id":"https://openalex.org/W7165851758","doi":"https://doi.org/10.48550/arxiv.2606.25680","title":"Average-Power-Budgeted Underwater Vehicle Control via Constrained Reinforcement Learning","display_name":"Average-Power-Budgeted Underwater Vehicle Control via Constrained Reinforcement Learning","publication_year":2026,"publication_date":"2026-06-24","ids":{"openalex":"https://openalex.org/W7165851758","doi":"https://doi.org/10.48550/arxiv.2606.25680"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.25680","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25680","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.2606.25680","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139327971","display_name":"Yinuo Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yinuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139366353","display_name":"Gavin Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Gavin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139360891","display_name":"Yuze Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yuze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Ringwood, John V.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ringwood, John V.","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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.4853000044822693,"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"}},"topics":[{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.4853000044822693,"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"}},{"id":"https://openalex.org/T10040","display_name":"Adaptive Control of Nonlinear Systems","score":0.07999999821186066,"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/T11250","display_name":"Wave and Wind Energy Systems","score":0.061900001019239426,"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/task","display_name":"Task (project management)","score":0.6165000200271606},{"id":"https://openalex.org/keywords/propulsion","display_name":"Propulsion","score":0.5620999932289124},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5458999872207642},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.5374000072479248},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.5371000170707703},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.534600019454956},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5302000045776367},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.5246000289916992},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5016999840736389},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4900999963283539}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6165000200271606},{"id":"https://openalex.org/C1034443","wikidata":"https://www.wikidata.org/wiki/Q2583685","display_name":"Propulsion","level":2,"score":0.5620999932289124},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5458999872207642},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.5371000170707703},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.534600019454956},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5302000045776367},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.5246000289916992},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5016999840736389},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4900999963283539},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4839000105857849},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48179998993873596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4781000018119812},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.46299999952316284},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4629000127315521},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.45410001277923584},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.39649999141693115},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C145424490","wikidata":"https://www.wikidata.org/wiki/Q618465","display_name":"Remotely operated underwater vehicle","level":4,"score":0.38109999895095825},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3684999942779541},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C56685638","wikidata":"https://www.wikidata.org/wiki/Q2300474","display_name":"Power control","level":3,"score":0.3197999894618988},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C76047896","wikidata":"https://www.wikidata.org/wiki/Q1786258","display_name":"Powertrain","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.28940001130104065},{"id":"https://openalex.org/C55660270","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C92018576","wikidata":"https://www.wikidata.org/wiki/Q3242194","display_name":"Power transmission","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C153240184","wikidata":"https://www.wikidata.org/wiki/Q3243772","display_name":"Control variable","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.25680","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25680","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.2606.25680","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25680","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":[{"display_name":"Affordable and clean energy","score":0.7465215921401978,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Underwater":[0],"vehicles":[1,166],"operate":[2],"from":[3,61],"a":[4,14,71,78,96,111,129,139,145,193,227],"fixed":[5],"onboard":[6],"energy":[7,59,220],"budget":[8,140],"that":[9,16,234],"propulsion":[10],"rapidly":[11],"depletes,":[12],"so":[13],"controller":[15],"completes":[17],"its":[18],"task":[19,44,211],"while":[20,202],"drawing":[21],"less":[22],"thruster":[23,119],"power":[24,80,120,133,180],"directly":[25],"extends":[26],"mission":[27],"range":[28],"and":[29,39,93,95,144,158,167,196,209],"endurance.":[30],"Reinforcement":[31],"learning":[32],"yields":[33],"capable":[34],"model-free":[35],"controllers":[36],"for":[37,90,155],"station-keeping":[38],"trajectory":[40],"tracking,":[41],"but":[42],"optimizing":[43],"accuracy":[45,212],"alone":[46],"drives":[47],"the":[48,62,67,85,171,174,178,204],"policy":[49,176],"toward":[50],"oscillatory,":[51],"energy-wasting":[52],"actuation.":[53],"The":[54,132],"established":[55],"remedy":[56],"subtracts":[57],"an":[58,124,198,222],"penalty":[60],"reward,":[63],"yet":[64],"this":[65],"sets":[66],"task-power":[68],"trade-off":[69],"through":[70],"single":[72,146],"weight":[73,86,98,162,239],"with":[74,128],"no":[75,236],"physical":[76,142],"units:":[77],"target":[79],"level":[81,134],"cannot":[82],"be":[83,88],"specified,":[84],"must":[87],"re-tuned":[89],"every":[91],"vehicle":[92,157],"task,":[94,159],"mismatched":[97],"can":[99],"even":[100],"raise":[101],"power.":[102],"This":[103],"paper":[104],"instead":[105],"formulates":[106],"energy-efficient":[107,231],"underwater":[108,232],"control":[109,233],"as":[110,221],"constrained":[112],"Markov":[113],"decision":[114],"process":[115],"in":[116,141,170,181,206,214],"which":[117],"average":[118],"is":[121,135,149],"subject":[122],"to":[123,152,190,230],"explicit":[125,223],"budget,":[126],"solved":[127],"PPO-Lagrangian":[130],"algorithm.":[131],"set":[136],"by":[137,187],"declaring":[138],"units,":[143],"dual":[147],"variable":[148],"updated":[150],"online":[151],"meet":[153],"it":[154,186],"each":[156],"without":[160],"manual":[161],"search.":[163,240],"Across":[164],"three":[165],"four":[168],"tasks":[169],"MarineGym":[172],"simulator,":[173],"energy-constrained":[175],"draws":[177],"least":[179],"all":[182],"twelve":[183],"settings,":[184],"reducing":[185],"14--65\\%":[188],"(up":[189],"64.9\\%)":[191],"over":[192],"task-only":[194],"baseline":[195,200],"below":[197],"energy-reward":[199],"everywhere,":[201],"remaining":[203],"smoothest":[205],"ten":[207],"settings":[208],"preserving":[210],"except":[213],"one":[215],"deliberately":[216],"power-limited":[217],"regime.":[218],"Imposing":[219],"constraint":[224],"thus":[225],"offers":[226],"tuning-free":[228],"route":[229],"needs":[235],"per-vehicle,":[237],"per-task":[238]},"counts_by_year":[],"updated_date":"2026-07-15T05:50:42.429089","created_date":"2026-06-26T00:00:00"}
