{"id":"https://openalex.org/W4405785252","doi":"https://doi.org/10.1109/iros58592.2024.10802063","title":"Indoor Position Estimation Using NLoS Reflected Path with Wireless Distance Sensors","display_name":"Indoor Position Estimation Using NLoS Reflected Path with Wireless Distance Sensors","publication_year":2024,"publication_date":"2024-10-14","ids":{"openalex":"https://openalex.org/W4405785252","doi":"https://doi.org/10.1109/iros58592.2024.10802063"},"language":"en","primary_location":{"id":"doi:10.1109/iros58592.2024.10802063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5028320286","display_name":"Tomoya ITSUKA","orcid":"https://orcid.org/0000-0002-9603-5691"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tomoya Itsuka","raw_affiliation_strings":["Kyushu University,Graduate School of Information Science and Electrical Engineering,Japan"],"affiliations":[{"raw_affiliation_string":"Kyushu University,Graduate School of Information Science and Electrical Engineering,Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073445963","display_name":"Ryo Kurazume","orcid":"https://orcid.org/0000-0002-4219-7644"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Kurazume","raw_affiliation_strings":["Kyushu University,Faculty of Information Science and Electrical Engineering,Japan"],"affiliations":[{"raw_affiliation_string":"Kyushu University,Faculty of Information Science and Electrical Engineering,Japan","institution_ids":["https://openalex.org/I135598925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5028320286"],"corresponding_institution_ids":["https://openalex.org/I135598925"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22618398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5573","last_page":"5580"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9926000237464905,"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":0.9926000237464905,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9438999891281128,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/non-line-of-sight-propagation","display_name":"Non-line-of-sight propagation","score":0.9166985750198364},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6221439242362976},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5906731486320496},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.546609103679657},{"id":"https://openalex.org/keywords/path-loss","display_name":"Path loss","score":0.4770083427429199},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4688880145549774},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.44327491521835327},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4226754307746887},{"id":"https://openalex.org/keywords/distance-measurement","display_name":"Distance measurement","score":0.4186226427555084},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34990209341049194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26787084341049194},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2604285776615143},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.233408123254776},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15585830807685852}],"concepts":[{"id":"https://openalex.org/C154910267","wikidata":"https://www.wikidata.org/wiki/Q1740982","display_name":"Non-line-of-sight propagation","level":3,"score":0.9166985750198364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6221439242362976},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5906731486320496},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.546609103679657},{"id":"https://openalex.org/C194273485","wikidata":"https://www.wikidata.org/wiki/Q1478845","display_name":"Path loss","level":3,"score":0.4770083427429199},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4688880145549774},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.44327491521835327},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4226754307746887},{"id":"https://openalex.org/C2986158284","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Distance measurement","level":2,"score":0.4186226427555084},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34990209341049194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26787084341049194},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2604285776615143},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.233408123254776},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15585830807685852},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros58592.2024.10802063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1990884907","https://openalex.org/W2057868216","https://openalex.org/W2060873147","https://openalex.org/W2154459632","https://openalex.org/W2482726005","https://openalex.org/W2530375805","https://openalex.org/W2567258865","https://openalex.org/W2766235398","https://openalex.org/W2968618534","https://openalex.org/W2968704747","https://openalex.org/W2968829478","https://openalex.org/W2969022059","https://openalex.org/W3129245057","https://openalex.org/W3134476633","https://openalex.org/W3206179892","https://openalex.org/W3208236196","https://openalex.org/W3212225065","https://openalex.org/W4318773452","https://openalex.org/W4321020571","https://openalex.org/W4389667936","https://openalex.org/W6912333589"],"related_works":["https://openalex.org/W4306950403","https://openalex.org/W22721396","https://openalex.org/W2253573804","https://openalex.org/W4300167711","https://openalex.org/W2806700348","https://openalex.org/W2963347964","https://openalex.org/W1994455657","https://openalex.org/W2168752585","https://openalex.org/W2982213597","https://openalex.org/W2988991102"],"abstract_inverted_index":{"Indoor":[0],"robot":[1,100,117,151],"localization":[2],"is":[3,101,118,140,170],"important":[4],"for":[5,58],"the":[6,83,88,91,95,99,105,109,113,116,125,129,132,136,143,150,155,164,168],"realization":[7],"of":[8,46,90,98,135],"autonomous":[9],"service":[10],"robots.":[11],"Various":[12],"studies":[13],"have":[14],"been":[15],"conducted":[16],"on":[17],"\"indoor":[18],"GPS\"":[19],"measurements":[20,42],"using":[21,72,154],"wireless":[22,73],"distance":[23,41,65,74,111,130],"sensors":[24],"such":[25],"as":[26,120,159],"ultrasonic":[27],"beacons.":[28],"However,":[29],"when":[30],"these":[31],"beacons":[32],"encounter":[33],"non-line-of-sight":[34],"(NLoS)":[35],"conditions":[36],"due":[37],"to":[38,66,103,115,123,131,142],"obstacles,":[39],"accurate":[40],"become":[43],"challenging":[44],"because":[45],"multipath":[47],"and":[48,64,108,157,196],"other":[49],"effects.":[50],"In":[51],"this":[52,191],"study,":[53],"we":[54],"propose":[55],"a":[56,61,121,160,176,183],"method":[57,78,169,184,192],"simultaneously":[59],"estimating":[60],"robot\u2019s":[62,84,144],"position":[63,85,152],"reflective":[67,133],"surfaces":[68],"in":[69,163,175],"an":[70],"environment":[71,178],"sensors.":[75],"The":[76],"proposed":[77],"can":[79],"estimate":[80],"not":[81,187],"only":[82],"but":[86],"also":[87],"reflection":[89,189],"beacon":[92,114,137],"signal.":[93],"First,":[94],"wheel":[96],"odometry":[97],"assumed":[102],"be":[104],"initial":[106],"value,":[107],"measured":[110],"from":[112,149],"used":[119,158],"factor":[122,126,165],"construct":[124],"graph.":[127,166],"Second,":[128],"surface":[134],"signal,":[138],"which":[139],"parallel":[141],"movement":[145],"plane,":[146],"was":[147],"estimated":[148],"sequence":[153],"GMM":[156],"noise":[161],"model":[162],"Finally,":[167],"evaluated":[171],"by":[172],"acquiring":[173],"data":[174],"real":[177],"with":[179,182],"obstacles.":[180],"Compared":[181],"that":[185],"does":[186],"consider":[188],"paths,":[190],"demonstrated":[193],"improved":[194],"accuracy":[195],"effectiveness.":[197]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
