{"id":"https://openalex.org/W4414270441","doi":"https://doi.org/10.1109/lra.2025.3611157","title":"Safety Meets Speed: Accelerated Neural MPC With Safety Guarantees and No Retraining","display_name":"Safety Meets Speed: Accelerated Neural MPC With Safety Guarantees and No Retraining","publication_year":2025,"publication_date":"2025-09-17","ids":{"openalex":"https://openalex.org/W4414270441","doi":"https://doi.org/10.1109/lra.2025.3611157"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2025.3611157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3611157","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","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/A5111051547","display_name":"Kaikai Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kaikai Wang","raw_affiliation_strings":["School of Future Technology, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Future Technology, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102894049","display_name":"Taixin Li","orcid":"https://orcid.org/0000-0001-8366-335X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxun Li","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673719","display_name":"Liang Xu","orcid":"https://orcid.org/0000-0001-8171-0247"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Xu","raw_affiliation_strings":["School of Future Technology, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Future Technology, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033355107","display_name":"Qinglei Hu","orcid":"https://orcid.org/0000-0002-5563-310X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinglei Hu","raw_affiliation_strings":["School of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088962631","display_name":"Keyou You","orcid":"https://orcid.org/0000-0003-4355-5340"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keyou You","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5111051547"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":2.3234,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89864856,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"10","issue":"11","first_page":"11411","last_page":"11418"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9490000009536743,"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/T10791","display_name":"Advanced Control Systems Optimization","score":0.9490000009536743,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9284999966621399,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10320","display_name":"Neural Networks and Applications","score":0.9154999852180481,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7332000136375427},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.6470000147819519},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5860999822616577},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5616000294685364},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.48159998655319214},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.48100000619888306},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.38100001215934753},{"id":"https://openalex.org/keywords/adaptive-control","display_name":"Adaptive control","score":0.3578999936580658},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3522999882698059}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7332000136375427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6965000033378601},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.6470000147819519},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5860999822616577},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5616000294685364},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.3578999936580658},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C3832189","wikidata":"https://www.wikidata.org/wiki/Q8588916","display_name":"Models of neural computation","level":3,"score":0.34860000014305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34150001406669617},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.32330000400543213},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.31690001487731934},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.30660000443458557},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27630001306533813},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2712000012397766},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25459998846054077},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2025.3611157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3611157","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5779413134","display_name":null,"funder_award_id":"62333011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7548196558","display_name":null,"funder_award_id":"62461160313","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8086930443","display_name":null,"funder_award_id":"62373239","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2065846434","https://openalex.org/W2096078692","https://openalex.org/W2560504659","https://openalex.org/W2842089854","https://openalex.org/W2887532679","https://openalex.org/W3015470607","https://openalex.org/W3095839831","https://openalex.org/W3115747676","https://openalex.org/W3131850807","https://openalex.org/W3135239772","https://openalex.org/W3204657926","https://openalex.org/W3207637958","https://openalex.org/W3208705304","https://openalex.org/W4293741188","https://openalex.org/W4294691749","https://openalex.org/W4321380998","https://openalex.org/W4378194787","https://openalex.org/W4385486339","https://openalex.org/W4386432124","https://openalex.org/W4389665353","https://openalex.org/W4405785279","https://openalex.org/W4407949249","https://openalex.org/W4407988010","https://openalex.org/W4414270441"],"related_works":[],"abstract_inverted_index":{"While":[0],"Model":[1,23],"Predictive":[2,24],"Control":[3,25,48],"(MPC)":[4],"enforces":[5],"safety":[6],"via":[7],"constraints,":[8],"its":[9],"real-time":[10],"execution":[11],"can":[12],"exceed":[13],"embedded":[14,155],"compute":[15],"budgets.":[16],"We":[17,55],"propose":[18],"a":[19,67,78],"Barrier-integrated":[20],"Adaptive":[21],"Neural":[22],"(BAN-MPC)":[26],"framework":[27],"that":[28,128],"synergizes":[29],"neural":[30,59,80,97,103],"networks'":[31],"fast":[32],"computation":[33,117],"with":[34,47,140],"MPC's":[35],"constraint-handling":[36],"capability.":[37],"To":[38],"ensure":[39],"strict":[40],"safety,":[41],"we":[42,76],"replace":[43],"traditional":[44,135],"Euclidean":[45],"distance":[46],"Barrier":[49],"Functions":[50],"(CBFs)":[51],"for":[52,112],"collision":[53],"avoidance.":[54],"integrate":[56],"an":[57,153],"offline-learned":[58],"value":[60,88,98],"function":[61,89,99],"into":[62],"the":[63,84,87,96,110],"optimization":[64],"objective":[65],"of":[66,86],"Short-horizon":[68],"MPC,":[69,136],"substantially":[70],"reducing":[71,115],"online":[72],"computational":[73],"complexity.":[74],"Additionally,":[75],"use":[77],"second":[79],"network":[81],"to":[82,90],"learn":[83],"sensitivity":[85,104],"system":[91],"parameters,":[92],"and":[93,114],"adaptively":[94],"adjust":[95],"based":[100],"on":[101,124],"this":[102],"when":[105],"model":[106,146],"parameters":[107],"change,":[108],"eliminating":[109],"need":[111],"retraining":[113],"offline":[116],"costs.":[118],"The":[119],"hardware":[120],"in-the-loop":[121],"(HIL)":[122],"experiments":[123],"Jetson":[125],"Nano":[126],"show":[127],"BAN-MPC":[129],"solves":[130],"200":[131],"times":[132],"faster":[133],"than":[134],"enabling":[137],"collision-free":[138],"navigation":[139],"control":[141],"error":[142],"below":[143],"5%":[144],"under":[145],"parameter":[147],"variations":[148],"within":[149],"15%,":[150],"making":[151],"it":[152],"effective":[154],"MPC":[156],"alternative.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
