{"id":"https://openalex.org/W4324290363","doi":"https://doi.org/10.1109/access.2023.3257185","title":"Learning-Based Path Planning Under Co-Safe Temporal Logic Specifications","display_name":"Learning-Based Path Planning Under Co-Safe Temporal Logic Specifications","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4324290363","doi":"https://doi.org/10.1109/access.2023.3257185"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3257185","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3257185","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10068514.pdf","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://ieeexplore.ieee.org/ielx7/6287639/6514899/10068514.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034975936","display_name":"Kyunghoon Cho","orcid":"https://orcid.org/0000-0002-4679-6660"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kyunghoon Cho","raw_affiliation_strings":["Department of Information and Telecommunication Engineering, Incheon National University, Incheon, South Korea","Department of Information and Telecommunication Engineering, Incheon National University, Inchoen, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4679-6660","affiliations":[{"raw_affiliation_string":"Department of Information and Telecommunication Engineering, Incheon National University, Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]},{"raw_affiliation_string":"Department of Information and Telecommunication Engineering, Incheon National University, Inchoen, South Korea","institution_ids":["https://openalex.org/I146429904"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5034975936"],"corresponding_institution_ids":["https://openalex.org/I146429904"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.9265,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76043853,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"25865","last_page":"25878"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998000264167786,"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":0.9998000264167786,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9884999990463257,"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/computer-science","display_name":"Computer science","score":0.709400475025177},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6730617880821228},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.582094132900238},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5581971406936646},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.5506347417831421},{"id":"https://openalex.org/keywords/search-tree","display_name":"Search tree","score":0.5348675847053528},{"id":"https://openalex.org/keywords/linear-temporal-logic","display_name":"Linear temporal logic","score":0.5024983882904053},{"id":"https://openalex.org/keywords/search-algorithm","display_name":"Search algorithm","score":0.4493902921676636},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4297771155834198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37915611267089844},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34007930755615234},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3233492374420166},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2580943703651428},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.20270955562591553},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1729191243648529}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.709400475025177},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6730617880821228},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.582094132900238},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5581971406936646},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5506347417831421},{"id":"https://openalex.org/C207024777","wikidata":"https://www.wikidata.org/wiki/Q621673","display_name":"Search tree","level":3,"score":0.5348675847053528},{"id":"https://openalex.org/C4777664","wikidata":"https://www.wikidata.org/wiki/Q1536492","display_name":"Linear temporal logic","level":2,"score":0.5024983882904053},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.4493902921676636},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4297771155834198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37915611267089844},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34007930755615234},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3233492374420166},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2580943703651428},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.20270955562591553},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1729191243648529},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3257185","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3257185","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10068514.pdf","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"},{"id":"pmh:oai:doaj.org/article:79f1fa442e2b4e7f85989036a11e4701","is_oa":true,"landing_page_url":"https://doaj.org/article/79f1fa442e2b4e7f85989036a11e4701","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 25865-25878 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3257185","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3257185","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10068514.pdf","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":[],"awards":[{"id":"https://openalex.org/G313143809","display_name":null,"funder_award_id":"NRF-2021R1G1A1014256","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321363","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4324290363.pdf","grobid_xml":"https://content.openalex.org/works/W4324290363.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1424654272","https://openalex.org/W1488782959","https://openalex.org/W1498432697","https://openalex.org/W1540883472","https://openalex.org/W1967294943","https://openalex.org/W1970269621","https://openalex.org/W1971086298","https://openalex.org/W1986417217","https://openalex.org/W1995626426","https://openalex.org/W2000359213","https://openalex.org/W2045481323","https://openalex.org/W2066953328","https://openalex.org/W2073548775","https://openalex.org/W2090528409","https://openalex.org/W2095901198","https://openalex.org/W2104241562","https://openalex.org/W2117927826","https://openalex.org/W2124623089","https://openalex.org/W2131064738","https://openalex.org/W2135301926","https://openalex.org/W2141789581","https://openalex.org/W2153813483","https://openalex.org/W2156123119","https://openalex.org/W2165364079","https://openalex.org/W2233446961","https://openalex.org/W2735511423","https://openalex.org/W2738842532","https://openalex.org/W2883952496","https://openalex.org/W2963439114","https://openalex.org/W3011646207","https://openalex.org/W3090725241","https://openalex.org/W3133653368","https://openalex.org/W3134179334","https://openalex.org/W3142077573","https://openalex.org/W3201276757","https://openalex.org/W3206295144","https://openalex.org/W4205757878","https://openalex.org/W4223418744","https://openalex.org/W6687045409","https://openalex.org/W6744627333"],"related_works":["https://openalex.org/W2789480285","https://openalex.org/W1976673004","https://openalex.org/W1971267722","https://openalex.org/W2402589461","https://openalex.org/W3094979732","https://openalex.org/W2037710955","https://openalex.org/W183780713","https://openalex.org/W2049361636","https://openalex.org/W2131923625","https://openalex.org/W1971361861"],"abstract_inverted_index":{"This":[0],"paper":[1,36],"presents":[2],"a":[3,56,72,120,135,140],"path":[4,47],"planning":[5,48],"algorithm":[6],"for":[7,82],"efficiently":[8,86],"generating":[9],"low-cost":[10,83,88,136],"trajectories":[11],"that":[12,59,75,130,148],"meet":[13],"mission":[14,142],"requirements":[15],"specified":[16],"in":[17,119],"Linear":[18],"Time":[19],"Logic":[20],"(LTL),":[21],"where":[22],"cost":[23],"functions":[24],"are":[25],"defined":[26],"throughout":[27],"the":[28,35,64,77,96,100,107,113,131,149,155],"configuration":[29],"space.":[30],"The":[31,50],"main":[32],"idea":[33],"of":[34],"is":[37,91,146],"to":[38,45,62,67,80,94],"increase":[39],"efficiency":[40],"by":[41],"adding":[42],"learning-based":[43],"extensions":[44],"sampling-based":[46],"algorithms.":[49],"proposed":[51,132,150],"method":[52,133],"includes":[53],"two":[54],"layers:":[55],"high-level":[57],"layer":[58,74],"determines":[60],"how":[61,93],"expand":[63],"search":[65,78,81,97,115,126],"tree":[66,79,98,116],"satisfy":[68],"logical":[69],"specifications":[70],"and":[71],"low-level":[73],"extends":[76],"trajectories.":[84],"To":[85],"find":[87],"trajectories,":[89],"it":[90,145],"learned":[92],"extend":[95],"from":[99],"data":[101],"via":[102],"deep":[103],"learning.":[104],"By":[105],"leveraging":[106],"conditional":[108],"variational":[109],"autoencoder,":[110],"we":[111],"learn":[112],"ideal":[114],"extension":[117],"distribution":[118],"given":[121,141],"situation,":[122],"which":[123],"increases":[124],"solution":[125],"efficiency.":[127],"Simulations":[128],"show":[129],"finds":[134],"trajectory":[137],"while":[138],"meeting":[139],"specification.":[143],"Furthermore,":[144],"confirmed":[147],"approach":[151],"performs":[152],"better":[153],"than":[154],"existing":[156],"methods.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":7}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}