{"id":"https://openalex.org/W7163996845","doi":"https://doi.org/10.48550/arxiv.2606.08136","title":"Learning Predictive Control with Deep Koopman Operators for Autonomous Vehicle Motion Planning","display_name":"Learning Predictive Control with Deep Koopman Operators for Autonomous Vehicle Motion Planning","publication_year":2026,"publication_date":"2026-06-06","ids":{"openalex":"https://openalex.org/W7163996845","doi":"https://doi.org/10.48550/arxiv.2606.08136"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.08136","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08136","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.2606.08136","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138266326","display_name":"Xinglong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinglong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042371596","display_name":"Yongqian Xiao","orcid":"https://orcid.org/0000-0002-1674-988X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Yongqian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038338684","display_name":"Haotian Cao","orcid":"https://orcid.org/0000-0001-5905-4116"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Haotian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138259630","display_name":"Xing Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138239649","display_name":"Xin Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138253997","display_name":"Xin Xu (11989)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xin","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/T11206","display_name":"Model Reduction and Neural Networks","score":0.35420000553131104,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.35420000553131104,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.18080000579357147,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10791","display_name":"Advanced Control Systems Optimization","score":0.07689999788999557,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.725600004196167},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6766999959945679},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6021000146865845},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5368000268936157},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.5109999775886536},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4821000099182129},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4336000084877014},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4318000078201294},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.42149999737739563},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4083999991416931}],"concepts":[{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.725600004196167},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6766999959945679},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6021000146865845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5846999883651733},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5368000268936157},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.5109999775886536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.504800021648407},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4821000099182129},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3903999924659729},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3813999891281128},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3752000033855438},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.31610000133514404},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.3116999864578247},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.2883000075817108},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C145565327","wikidata":"https://www.wikidata.org/wiki/Q852514","display_name":"Motion control","level":3,"score":0.2865999937057495},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.25270000100135803},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.08136","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08136","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.2606.08136","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08136","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":[{"score":0.47660747170448303,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Model":[0],"Predictive":[1],"Control":[2],"(MPC)":[3],"is":[4,16,88],"widely":[5],"used":[6,89],"for":[7,22,44,70],"autonomous-vehicle":[8],"(AV)":[9],"motion":[10,73],"planning,":[11],"but":[12],"its":[13,49],"real-time":[14,72],"applicability":[15],"often":[17,52],"limited":[18],"by":[19],"the":[20,92,112,158,172],"need":[21],"accurate":[23],"models":[24],"and":[25,81,144,151,168,188,198],"online":[26,45],"solution":[27],"of":[28,142,184],"nonlinear,":[29],"nonconvex":[30,76,133],"optimization":[31],"problems":[32],"in":[33,100,178,182],"dynamic":[34],"road":[35],"environments.":[36],"Actor-critic":[37],"reinforcement":[38],"learning":[39,61],"offers":[40],"a":[41,60,85,101,117],"promising":[42],"alternative":[43],"policy":[46,120,164],"generation,":[47],"yet":[48],"policy-learning":[50],"process":[51],"lacks":[53],"explicit":[54],"control-theoretic":[55],"structure.":[56],"This":[57],"article":[58],"proposes":[59],"predictive":[62],"control":[63,110],"(LPC)":[64],"framework":[65,115],"with":[66,192],"deep":[67],"Koopman":[68],"operators":[69],"efficient":[71],"planning":[74],"under":[75,132],"constraints.":[77],"To":[78,129],"address":[79],"nonlinear":[80],"uncertain":[82],"vehicle":[83],"dynamics,":[84],"deep-Koopman-based":[86],"predictor":[87],"to":[90],"lift":[91],"system":[93],"into":[94,157],"an":[95],"interpretable":[96],"linear":[97],"observable":[98],"space":[99],"data-driven":[102],"manner.":[103],"Unlike":[104],"traditional":[105],"MPC,":[106],"which":[107],"computes":[108],"open-loop":[109],"sequences,":[111],"proposed":[113],"LPC":[114,136],"yields":[116],"closed-loop":[118],"state-feedback":[119],"within":[121],"each":[122],"prediction":[123],"interval":[124],"through":[125],"receding-horizon":[126],"actor-critic":[127,159],"learning.":[128,165],"ensure":[130],"safety":[131],"environmental":[134],"constraints,":[135],"constructs":[137],"convex":[138],"local":[139],"surrogate":[140],"representations":[141],"obstacles":[143],"defines":[145],"corresponding":[146],"potential-field":[147],"functions.":[148],"These":[149],"functions":[150],"their":[152],"gradients":[153],"are":[154],"directly":[155],"embedded":[156],"structure,":[160],"enabling":[161],"efficient,":[162],"safety-aware":[163],"Extensive":[166],"simulations":[167],"real-world":[169],"experiments":[170],"on":[171],"HongQi-EHS3":[173],"platform":[174],"demonstrate":[175],"favorable":[176],"performance":[177],"diverse":[179],"obstacle-avoidance":[180],"scenarios":[181],"terms":[183],"safety,":[185],"computational":[186],"efficiency,":[187],"driving":[189],"comfort,":[190],"compared":[191],"benchmark":[193],"methods":[194],"such":[195],"as":[196],"CBF-MPC":[197],"LMPCC.":[199]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}