{"id":"https://openalex.org/W3210343264","doi":"https://doi.org/10.1109/itsc48978.2021.9564908","title":"A Gaussian approximation of the posterior for digital map-based localization using a particle filter","display_name":"A Gaussian approximation of the posterior for digital map-based localization using a particle filter","publication_year":2021,"publication_date":"2021-09-19","ids":{"openalex":"https://openalex.org/W3210343264","doi":"https://doi.org/10.1109/itsc48978.2021.9564908","mag":"3210343264"},"language":"en","primary_location":{"id":"doi:10.1109/itsc48978.2021.9564908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-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/A5089355384","display_name":"Andr\u00e9 Przewodowski","orcid":"https://orcid.org/0000-0002-4120-8540"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]},{"id":"https://openalex.org/I4210131883","display_name":"Brazilian Society of Computational and Applied Mathematics","ror":"https://ror.org/03kcw4w74","country_code":"BR","type":"other","lineage":["https://openalex.org/I4210131883"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Andre Przewodowski","raw_affiliation_strings":["Laborat\u00f3rio de Rob\u00f3tica M\u00f3vel (LRM) of the Instituto de Ci\u00eancias Matem\u00e1ticas e de Computa\u00e7\u00e3o (ICMC), Universidade de S\u00e3o Paulo (USP), S\u00e3o Carlos, (SP), Brazil"],"affiliations":[{"raw_affiliation_string":"Laborat\u00f3rio de Rob\u00f3tica M\u00f3vel (LRM) of the Instituto de Ci\u00eancias Matem\u00e1ticas e de Computa\u00e7\u00e3o (ICMC), Universidade de S\u00e3o Paulo (USP), S\u00e3o Carlos, (SP), Brazil","institution_ids":["https://openalex.org/I4210131883","https://openalex.org/I17974374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030595758","display_name":"Fernando Santos Os\u00f3rio","orcid":"https://orcid.org/0000-0002-6620-2794"},"institutions":[{"id":"https://openalex.org/I4210131883","display_name":"Brazilian Society of Computational and Applied Mathematics","ror":"https://ror.org/03kcw4w74","country_code":"BR","type":"other","lineage":["https://openalex.org/I4210131883"]},{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fernando Santos Osorio","raw_affiliation_strings":["Laborat\u00f3rio de Rob\u00f3tica M\u00f3vel (LRM) of the Instituto de Ci\u00eancias Matem\u00e1ticas e de Computa\u00e7\u00e3o (ICMC), Universidade de S\u00e3o Paulo (USP), S\u00e3o Carlos, (SP), Brazil"],"affiliations":[{"raw_affiliation_string":"Laborat\u00f3rio de Rob\u00f3tica M\u00f3vel (LRM) of the Instituto de Ci\u00eancias Matem\u00e1ticas e de Computa\u00e7\u00e3o (ICMC), Universidade de S\u00e3o Paulo (USP), S\u00e3o Carlos, (SP), Brazil","institution_ids":["https://openalex.org/I4210131883","https://openalex.org/I17974374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089355384"],"corresponding_institution_ids":["https://openalex.org/I17974374","https://openalex.org/I4210131883"],"apc_list":null,"apc_paid":null,"fwci":0.1003,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44425682,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"3026","last_page":"3033"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.7282910346984863},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6723653078079224},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6387483477592468},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.608553409576416},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.5752944350242615},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5229478478431702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.522038459777832},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49705055356025696},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.46113717555999756},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.4526597261428833},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.42947518825531006},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4256954789161682},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.42111608386039734},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.41720354557037354},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.40701112151145935},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3715892434120178},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25205814838409424},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16033008694648743}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7282910346984863},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6723653078079224},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6387483477592468},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.608553409576416},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.5752944350242615},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5229478478431702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.522038459777832},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49705055356025696},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.46113717555999756},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.4526597261428833},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.42947518825531006},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4256954789161682},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.42111608386039734},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41720354557037354},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.40701112151145935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3715892434120178},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25205814838409424},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16033008694648743},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc48978.2021.9564908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.800000011920929,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W301022506","https://openalex.org/W1686810756","https://openalex.org/W2130422193","https://openalex.org/W2161969291","https://openalex.org/W2168676389","https://openalex.org/W2292739518","https://openalex.org/W2296267969","https://openalex.org/W2408871235","https://openalex.org/W2554361746","https://openalex.org/W2796347433","https://openalex.org/W2901136733","https://openalex.org/W2967975754","https://openalex.org/W4293584584","https://openalex.org/W6697114518","https://openalex.org/W6756486208"],"related_works":["https://openalex.org/W2944823289","https://openalex.org/W3037018281","https://openalex.org/W2003209439","https://openalex.org/W4321854979","https://openalex.org/W2358319515","https://openalex.org/W2972592048","https://openalex.org/W4312214821","https://openalex.org/W2497626292","https://openalex.org/W4252024964","https://openalex.org/W4253883008"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"an":[5,140],"importance":[6],"sampling-based":[7],"localization":[8,130],"method":[9,125],"that":[10,89,123],"approximates":[11],"the":[12,26,32,37,46,53,93,124],"belief":[13],"to":[14,68,92,139],"a":[15,129],"Gaussian":[16],"distribution":[17],"after":[18],"update":[19],"for":[20,30,64,128],"digital":[21,38],"map-based":[22],"localization.":[23],"It":[24],"uses":[25],"planned":[27],"route":[28],"information":[29],"constraining":[31],"map":[33,39],"possibilities":[34],"and":[35,41,96,134,143],"matches":[36],"features":[40,43,88],"higher":[42],"detected":[44],"by":[45],"vehicle.":[47],"This":[48],"approach":[49],"does":[50,57],"not":[51,58],"constrain":[52],"vehicle's":[54],"sensor":[55],"setup,":[56],"require":[59],"as":[60],"much":[61],"human":[62],"effort":[63],"mapping":[65],"when":[66,100,112],"compared":[67],"High":[69],"Definition":[70],"(HD)":[71],"maps,":[72],"is":[73,97,102,110,126],"relatively":[74],"more":[75,107],"resilient":[76],"than":[77],"low":[78],"level":[79],"point":[80],"cloud":[81],"approaches":[82],"since":[83],"it":[84,101],"can":[85],"rely":[86],"on":[87],"are":[90,144],"relative":[91],"city":[94],"structure,":[95],"self-aware":[98],"of":[99],"uncertain":[103],"between":[104],"two":[105],"or":[106],"modes,":[108],"which":[109],"useful":[111],"fusing":[113],"with":[114],"other":[115],"state":[116],"estimation":[117],"methods.":[118],"The":[119,132],"conducted":[120],"experiments":[121],"suggest":[122],"adequate":[127],"pipeline.":[131],"code":[133],"dataset":[135],"used":[136],"were":[137],"uploaded":[138],"online":[141],"repository":[142],"open-access.":[145]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
