{"id":"https://openalex.org/W1982513898","doi":"https://doi.org/10.1109/cca.2014.6981509","title":"Vehicle localization by sensor fusion of LRS measurement and odometry information based on moving horizon estimation","display_name":"Vehicle localization by sensor fusion of LRS measurement and odometry information based on moving horizon estimation","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W1982513898","doi":"https://doi.org/10.1109/cca.2014.6981509","mag":"1982513898"},"language":"en","primary_location":{"id":"doi:10.1109/cca.2014.6981509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cca.2014.6981509","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Conference on Control Applications (CCA)","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/A5031670083","display_name":"Kazuki Kimura","orcid":"https://orcid.org/0000-0003-3681-6821"},"institutions":[{"id":"https://openalex.org/I185088104","display_name":"Tokyo City University","ror":"https://ror.org/04dt6bw53","country_code":"JP","type":"education","lineage":["https://openalex.org/I185088104"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kazuki Kimura","raw_affiliation_strings":["Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","institution_ids":["https://openalex.org/I185088104"]},{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan","institution_ids":["https://openalex.org/I185088104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001112845","display_name":"Yutaro Hiromachi","orcid":null},"institutions":[{"id":"https://openalex.org/I185088104","display_name":"Tokyo City University","ror":"https://ror.org/04dt6bw53","country_code":"JP","type":"education","lineage":["https://openalex.org/I185088104"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaro Hiromachi","raw_affiliation_strings":["Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","institution_ids":["https://openalex.org/I185088104"]},{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan","institution_ids":["https://openalex.org/I185088104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068258996","display_name":"Kenichiro Nonaka","orcid":"https://orcid.org/0000-0003-0532-0495"},"institutions":[{"id":"https://openalex.org/I185088104","display_name":"Tokyo City University","ror":"https://ror.org/04dt6bw53","country_code":"JP","type":"education","lineage":["https://openalex.org/I185088104"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenichiro Nonaka","raw_affiliation_strings":["Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","institution_ids":["https://openalex.org/I185088104"]},{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan","institution_ids":["https://openalex.org/I185088104"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065997102","display_name":"Kazuma Sekiguchi","orcid":"https://orcid.org/0000-0001-6502-0617"},"institutions":[{"id":"https://openalex.org/I185088104","display_name":"Tokyo City University","ror":"https://ror.org/04dt6bw53","country_code":"JP","type":"education","lineage":["https://openalex.org/I185088104"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuma Sekiguchi","raw_affiliation_strings":["Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, Setagaya, Tokyo, Japan","institution_ids":["https://openalex.org/I185088104"]},{"raw_affiliation_string":"Department of Mechanical Systems Engineering, Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan","institution_ids":["https://openalex.org/I185088104"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031670083"],"corresponding_institution_ids":["https://openalex.org/I185088104"],"apc_list":null,"apc_paid":null,"fwci":2.4541,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.90350435,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2014","issue":null,"first_page":"1306","last_page":"1311"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9976000189781189,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.9299285411834717},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7406677603721619},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6945070624351501},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6811534762382507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6746856570243835},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6224237084388733},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.57826167345047},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.46868517994880676},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.44926923513412476},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.44735538959503174},{"id":"https://openalex.org/keywords/information-fusion","display_name":"Information fusion","score":0.4452534317970276},{"id":"https://openalex.org/keywords/distance-measurement","display_name":"Distance measurement","score":0.4293109178543091},{"id":"https://openalex.org/keywords/observational-error","display_name":"Observational error","score":0.4172772765159607},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.2024017870426178},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19671586155891418},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.18175029754638672},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16835322976112366},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08083280920982361}],"concepts":[{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.9299285411834717},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7406677603721619},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6945070624351501},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6811534762382507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6746856570243835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6224237084388733},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.57826167345047},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.46868517994880676},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.44926923513412476},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.44735538959503174},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.4452534317970276},{"id":"https://openalex.org/C2986158284","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Distance measurement","level":2,"score":0.4293109178543091},{"id":"https://openalex.org/C19619285","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Observational error","level":2,"score":0.4172772765159607},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.2024017870426178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19671586155891418},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.18175029754638672},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16835322976112366},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08083280920982361},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cca.2014.6981509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cca.2014.6981509","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Conference on Control Applications (CCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321672","display_name":"Else Kr\u00f6ner-Fresenius-Stiftung","ror":"https://ror.org/03zcxha54"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1537329839","https://openalex.org/W1870572154","https://openalex.org/W2030843275","https://openalex.org/W2052345359","https://openalex.org/W2058758563","https://openalex.org/W2072776923","https://openalex.org/W2086059115","https://openalex.org/W2098023159","https://openalex.org/W2115482885","https://openalex.org/W2117402460","https://openalex.org/W2121055419","https://openalex.org/W2125631815","https://openalex.org/W2129276668","https://openalex.org/W2132521546","https://openalex.org/W2132631693","https://openalex.org/W2147753640","https://openalex.org/W2149426093","https://openalex.org/W2159456898","https://openalex.org/W2165468899","https://openalex.org/W2331134302","https://openalex.org/W2336416123","https://openalex.org/W2397055207","https://openalex.org/W4285719527","https://openalex.org/W6674879571","https://openalex.org/W6679942759","https://openalex.org/W6712576334"],"related_works":["https://openalex.org/W3088112989","https://openalex.org/W2392793229","https://openalex.org/W2048373740","https://openalex.org/W2103761320","https://openalex.org/W2348824220","https://openalex.org/W3028432408","https://openalex.org/W2136123817","https://openalex.org/W2608696184","https://openalex.org/W2166350757","https://openalex.org/W2769041751"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3],"propose":[4],"a":[5,24,51],"localization":[6,58,77,90],"method":[7,59],"based":[8],"on":[9,76],"the":[10,13,20,38,69,79,86],"fusion":[11],"of":[12,23,42,71,81,88],"laser":[14],"range":[15],"sensor":[16],"(LRS)":[17],"measurements":[18],"and":[19,35,73,94],"odometry":[21],"information":[22],"vehicle":[25,52],"using":[26,78],"moving":[27],"horizon":[28],"estimation":[29],"(MHE).":[30],"LRS":[31],"measurement":[32],"includes":[33],"outliers":[34,72],"suffers":[36],"from":[37],"intermittent":[39,74],"observation;":[40],"alleviation":[41],"their":[43],"effect":[44,70],"is":[45],"required":[46],"in":[47],"order":[48],"to":[49],"localize":[50],"position":[53],"with":[54],"high":[55],"accuracy.":[56],"Proposed":[57],"merges":[60],"multi-sampling":[61],"data":[62,80],"by":[63,91],"exploiting":[64],"MHE,":[65],"which":[66],"greatly":[67],"reduces":[68],"observation":[75],"other":[82],"sampling.":[83],"We":[84],"show":[85],"efficacy":[87],"proposed":[89],"numerical":[92],"simulations":[93],"experiments.":[95]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
