{"id":"https://openalex.org/W4220748700","doi":"https://doi.org/10.1109/sii52469.2022.9708872","title":"Diagnosing Deep SLAM for Domain-Shift Localization","display_name":"Diagnosing Deep SLAM for Domain-Shift Localization","publication_year":2022,"publication_date":"2022-01-09","ids":{"openalex":"https://openalex.org/W4220748700","doi":"https://doi.org/10.1109/sii52469.2022.9708872"},"language":"en","primary_location":{"id":"doi:10.1109/sii52469.2022.9708872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii52469.2022.9708872","pdf_url":null,"source":{"id":"https://openalex.org/S4363605592","display_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5104084387","display_name":"Mitsuki Yoshida","orcid":null},"institutions":[{"id":"https://openalex.org/I111966504","display_name":"University of Fukui","ror":"https://ror.org/00msqp585","country_code":"JP","type":"education","lineage":["https://openalex.org/I111966504"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshida Mitsuki","raw_affiliation_strings":["Robotics Course, University of Fukui, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Course, University of Fukui, Japan","institution_ids":["https://openalex.org/I111966504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007423029","display_name":"Tanaka Kanji","orcid":"https://orcid.org/0000-0002-1143-5478"},"institutions":[{"id":"https://openalex.org/I111966504","display_name":"University of Fukui","ror":"https://ror.org/00msqp585","country_code":"JP","type":"education","lineage":["https://openalex.org/I111966504"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tanaka Kanji","raw_affiliation_strings":["Robotics Course, University of Fukui, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Course, University of Fukui, Japan","institution_ids":["https://openalex.org/I111966504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111966504"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01576851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"724","last_page":"729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9997000098228455,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10653","display_name":"Robot Manipulation and Learning","score":0.9848999977111816,"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/computer-science","display_name":"Computer science","score":0.7533750534057617},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7483125925064087},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6279879808425903},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.6002311706542969},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.5732216238975525},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5432712435722351},{"id":"https://openalex.org/keywords/workspace","display_name":"Workspace","score":0.5191347002983093},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.45305436849594116},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4525182247161865},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43929606676101685},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.41381973028182983},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.33195924758911133}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7533750534057617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7483125925064087},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6279879808425903},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.6002311706542969},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.5732216238975525},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5432712435722351},{"id":"https://openalex.org/C58581272","wikidata":"https://www.wikidata.org/wiki/Q12741163","display_name":"Workspace","level":3,"score":0.5191347002983093},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.45305436849594116},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4525182247161865},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43929606676101685},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.41381973028182983},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.33195924758911133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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":1,"locations":[{"id":"doi:10.1109/sii52469.2022.9708872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii52469.2022.9708872","pdf_url":null,"source":{"id":"https://openalex.org/S4363605592","display_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5123141126","display_name":"The realization of next-generation SLAM technique based on self-diagnosis map: maintenance-free SLAM","funder_award_id":"20K12008","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W1498436455","https://openalex.org/W1543742640","https://openalex.org/W1686810756","https://openalex.org/W1738827650","https://openalex.org/W1957167950","https://openalex.org/W1982696459","https://openalex.org/W1999399477","https://openalex.org/W2071534836","https://openalex.org/W2114309107","https://openalex.org/W2122143990","https://openalex.org/W2124732125","https://openalex.org/W2160650656","https://openalex.org/W2598706937","https://openalex.org/W2606327391","https://openalex.org/W2750632489","https://openalex.org/W2883823472","https://openalex.org/W2963221299","https://openalex.org/W2991479749","https://openalex.org/W3013299216","https://openalex.org/W3106440972","https://openalex.org/W6637373629","https://openalex.org/W6640926891","https://openalex.org/W6732973827"],"related_works":["https://openalex.org/W1992503747","https://openalex.org/W2970345194","https://openalex.org/W2161240633","https://openalex.org/W4386821976","https://openalex.org/W4313288997","https://openalex.org/W2807473852","https://openalex.org/W2149015029","https://openalex.org/W48401697","https://openalex.org/W2152464524","https://openalex.org/W2556215627"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3,33,126],"address":[4],"a":[5,16,21,35,40,46,60,128,156,174],"novel":[6,129],"\"domain-shift":[7],"localization":[8],"(DSL)\"":[9],"problem,":[10],"by":[11],"which":[12,112],"\"user":[13],"robots\"":[14,65],"of":[15,90,97,122,145],"deep":[17,42,101,105,158,169],"SLAM":[18,43,98,102,123,159,170],"system":[19,44,103,160],"localize":[20],"domain-shifted":[22,78],"region":[23],"in":[24,76],"the":[25,77,82,88,100,119,142,167,181],"robot":[26],"workspace":[27],"during":[28],"their":[29],"daily":[30],"navigation.":[31],"Furthermore,":[32],"present":[34,127],"case":[36],"study":[37],"pertaining":[38],"to":[39,66,116,149,180],"simple":[41],"comprising":[45],"visual":[47,51],"place":[48],"classifier":[49],"and":[50,55,74],"odometry":[52],"as":[53,147],"exteroceptive":[54],"proprioceptive":[56],"modules,":[57],"respectively.":[58],"Such":[59],"DSL":[61],"method":[62],"enables":[63],"\"mapper":[64],"focus":[67],"on":[68,136],"available":[69],"resources":[70],"(e.g.,":[71],"time,":[72],"energy,":[73],"computation)":[75],"region,":[79],"rather":[80],"than":[81],"entire":[83],"workspace,":[84],"thereby":[85],"significantly":[86],"reducing":[87],"cost":[89],"per-domain":[91],"DNN":[92],"maintenance.":[93],"Unlike":[94],"conventional":[95],"scenarios":[96],"diagnosis,":[99,166],"comprises":[104],"neural":[106],"networks":[107],"(DNNs)":[108],"with":[109,155],"black-box":[110],"characteristics,":[111],"render":[113],"it":[114],"difficult":[115],"directly":[117],"diagnose":[118],"internal":[120,137],"signals":[121,138,144],"modules.":[124],"Hence,":[125],"diagnosis":[130],"algorithm":[131],"that":[132,161,176],"does":[133,162],"not":[134,163],"rely":[135],"but":[139],"uses":[140],"only":[141],"input/output":[143],"DNNs":[146],"input":[148],"DSL.":[150],"Experiments":[151],"demonstrate":[152],"that,":[153],"compared":[154],"vanilla":[157],"reflect":[164],"fault":[165],"proposed":[168],"framework":[171],"can":[172],"achieve":[173],"path":[175],"is":[177],"more":[178],"similar":[179],"actual":[182],"measured":[183],"GPS":[184],"path.":[185]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
