{"id":"https://openalex.org/W4414538273","doi":"https://doi.org/10.1109/jiot.2025.3614857","title":"Safety-Critical Path Planning for Obstacle Avoidance Based on Reinforcement Learning and Control Barrier Functions","display_name":"Safety-Critical Path Planning for Obstacle Avoidance Based on Reinforcement Learning and Control Barrier Functions","publication_year":2025,"publication_date":"2025-09-26","ids":{"openalex":"https://openalex.org/W4414538273","doi":"https://doi.org/10.1109/jiot.2025.3614857"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2025.3614857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3614857","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5021696051","display_name":"Zhenyu Xu","orcid":"https://orcid.org/0000-0003-1049-6700"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Xu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040414354","display_name":"Ke Wang","orcid":"https://orcid.org/0000-0002-8306-1663"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Wang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8306-1663","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057898837","display_name":"Chaoxu Mu","orcid":"https://orcid.org/0000-0003-1055-9513"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoxu Mu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-1055-9513","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037428599","display_name":"Tie Qiu","orcid":"https://orcid.org/0000-0003-2324-2523"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tie Qiu","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0003-2324-2523","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.5444,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.96597998,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"12","issue":"23","first_page":"51410","last_page":"51421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9991999864578247,"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":0.9991999864578247,"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/T10879","display_name":"Robotic Locomotion and Control","score":0.965399980545044,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T13382","display_name":"Robotics and Automated Systems","score":0.9459999799728394,"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/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.800599992275238},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.6593999862670898},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6283000111579895},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.5748999714851379},{"id":"https://openalex.org/keywords/quadratic-programming","display_name":"Quadratic programming","score":0.5425999760627747},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.44530001282691956},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4226999878883362},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4180999994277954},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.3955000042915344},{"id":"https://openalex.org/keywords/robust-control","display_name":"Robust control","score":0.3882000148296356}],"concepts":[{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.800599992275238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6919000148773193},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.6593999862670898},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6283000111579895},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.5748999714851379},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.5425999760627747},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.44530001282691956},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4327999949455261},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4226999878883362},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4180999994277954},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C31531917","wikidata":"https://www.wikidata.org/wiki/Q915157","display_name":"Robust control","level":3,"score":0.3882000148296356},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C145565327","wikidata":"https://www.wikidata.org/wiki/Q852514","display_name":"Motion control","level":3,"score":0.367000013589859},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C3031470","wikidata":"https://www.wikidata.org/wiki/Q818544","display_name":"State observer","level":3,"score":0.36419999599456787},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C198927703","wikidata":"https://www.wikidata.org/wiki/Q4373881","display_name":"Sequential quadratic programming","level":3,"score":0.32260000705718994},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.2831000089645386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.27810001373291016},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2529999911785126},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3614857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3614857","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1658263654","display_name":null,"funder_award_id":"2024ZY009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7045126158","display_name":null,"funder_award_id":"2024M752364","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G751832858","display_name":null,"funder_award_id":"62333016","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1601719319","https://openalex.org/W1614417283","https://openalex.org/W1980569135","https://openalex.org/W1983523797","https://openalex.org/W2107122393","https://openalex.org/W2292762495","https://openalex.org/W2306644740","https://openalex.org/W2333120204","https://openalex.org/W2341848647","https://openalex.org/W2524886531","https://openalex.org/W2560504659","https://openalex.org/W2588802774","https://openalex.org/W2912361519","https://openalex.org/W2921905705","https://openalex.org/W3094402048","https://openalex.org/W3114263192","https://openalex.org/W3154507809","https://openalex.org/W3186317065","https://openalex.org/W3201167150","https://openalex.org/W4206273786","https://openalex.org/W4206494026","https://openalex.org/W4226255370","https://openalex.org/W4283016194","https://openalex.org/W4285108207","https://openalex.org/W4312581147","https://openalex.org/W4321609042","https://openalex.org/W4367016244","https://openalex.org/W4384303949","https://openalex.org/W4385236825","https://openalex.org/W4386432124","https://openalex.org/W4388283392","https://openalex.org/W4389403307","https://openalex.org/W4390776833","https://openalex.org/W4392251589","https://openalex.org/W4393285734","https://openalex.org/W4399800787","https://openalex.org/W4401163789","https://openalex.org/W4401247288","https://openalex.org/W4404370981","https://openalex.org/W4405754419","https://openalex.org/W4407127499","https://openalex.org/W4407901494","https://openalex.org/W4409102111","https://openalex.org/W4409580949","https://openalex.org/W4410852502"],"related_works":[],"abstract_inverted_index":{"This":[0],"article":[1],"presents":[2],"a":[3,34,46,55,63,80,102,120,136],"safety-critical":[4,115],"control":[5,29,150],"framework":[6,124],"for":[7],"navigation":[8],"in":[9,181],"complex":[10],"environments":[11],"with":[12,28,45],"numerous":[13],"obstacles.":[14],"An":[15],"online":[16],"robust":[17],"path":[18,157],"planning":[19],"scheme":[20,165],"is":[21,37,58,69,99,152,166],"developed":[22],"by":[23,71,78,110],"integrating":[24],"reinforcement":[25],"learning":[26,85],"(RL)":[27],"barrier":[30],"functions":[31],"(CBFs).":[32],"First,":[33],"disturbance":[35,43],"observer":[36],"designed":[38,59],"to":[39,125],"estimate":[40],"the":[41,51,84,113,127,160,163,175,178],"unknown":[42],"along":[44],"derived":[47],"upper":[48],"bound":[49],"of":[50,106,162],"estimation":[52],"error.":[53],"Then,":[54,146],"nominal":[56,128],"controller":[57],"using":[60,72,139],"RL,":[61],"where":[62],"critic":[64],"neural":[65],"network":[66],"(NN)":[67],"structure":[68],"established":[70],"state-following":[73],"(StaF)":[74],"kernel":[75],"function.":[76],"Additionally,":[77],"employing":[79],"state":[81],"extrapolation":[82],"technique,":[83],"process":[86],"leverages":[87],"both":[88],"real-time":[89],"and":[90,171],"simulated":[91],"experience":[92],"data.":[93],"To":[94],"ensure":[95],"safety,":[96],"obstacle":[97],"avoidance":[98],"formulated":[100],"as":[101],"forward":[103],"invariance":[104],"problem":[105],"safe":[107,149],"sets":[108],"defined":[109],"CBFs.":[111],"Subsequently,":[112],"CBF-based":[114],"constraints":[116],"are":[117,133],"integrated":[118],"into":[119,135],"quadratic":[121],"programming":[122],"(QP)":[123],"modify":[126],"controller.":[129],"Furthermore,":[130],"these":[131],"CBFs":[132],"incorporated":[134],"composite":[137],"CBF":[138],"smooth":[140],"approximation,":[141],"enabling":[142],"efficient":[143],"constraint":[144],"consolidation.":[145],"an":[147],"explicit":[148],"policy":[151],"proposed":[153,164],"that":[154],"guarantees":[155],"collision-free":[156],"planning.":[158],"Finally,":[159],"effectiveness":[161],"demonstrated":[167],"through":[168],"numerical":[169],"simulations,":[170],"comparative":[172],"results":[173],"show":[174],"advantages":[176],"over":[177],"existing":[179],"methods":[180],"motion":[182],"trajectory.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2025-10-10T00:00:00"}
