{"id":"https://openalex.org/W2970961077","doi":"https://doi.org/10.1109/icinfa.2018.8812403","title":"An IMU-aided Visual Odometry with Loop-closure Optimization","display_name":"An IMU-aided Visual Odometry with Loop-closure Optimization","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2970961077","doi":"https://doi.org/10.1109/icinfa.2018.8812403","mag":"2970961077"},"language":"en","primary_location":{"id":"doi:10.1109/icinfa.2018.8812403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2018.8812403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Information and Automation (ICIA)","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/A5100697230","display_name":"Yue Mei","orcid":"https://orcid.org/0000-0003-3469-3055"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Mei","raw_affiliation_strings":["School of Electronic Information and Engineering, Beijing Jiao Tong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Engineering, Beijing Jiao Tong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100674334","display_name":"Zhongli Wang","orcid":"https://orcid.org/0000-0002-3236-8219"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongli Wang","raw_affiliation_strings":["School of Electronic Information and Engineering, Beijing Jiao Tong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Engineering, Beijing Jiao Tong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100636115","display_name":"Baigen Cai","orcid":"https://orcid.org/0000-0002-6440-005X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baigen Cai","raw_affiliation_strings":["School of Electronic Information and Engineering, Beijing Jiao Tong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Engineering, Beijing Jiao Tong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31925137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1444","last_page":"1449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7699978351593018},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.760858416557312},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.7460535764694214},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7452871799468994},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.7240038514137268},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6774038076400757},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.6751369833946228},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.5715447664260864},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.53020179271698},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4242822229862213},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4100847542285919},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.30688923597335815}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7699978351593018},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.760858416557312},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.7460535764694214},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7452871799468994},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.7240038514137268},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6774038076400757},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.6751369833946228},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5715447664260864},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.53020179271698},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4242822229862213},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4100847542285919},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.30688923597335815},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icinfa.2018.8812403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2018.8812403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Information and Automation (ICIA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W25933536","https://openalex.org/W1521470386","https://openalex.org/W1557515246","https://openalex.org/W1677409904","https://openalex.org/W1972671602","https://openalex.org/W1974093076","https://openalex.org/W1981699551","https://openalex.org/W2024676408","https://openalex.org/W2056358962","https://openalex.org/W2073459066","https://openalex.org/W2082312667","https://openalex.org/W2108023813","https://openalex.org/W2114858887","https://openalex.org/W2117228865","https://openalex.org/W2118223742","https://openalex.org/W2124386111","https://openalex.org/W2131846894","https://openalex.org/W2133759223","https://openalex.org/W2148820580","https://openalex.org/W2264705868","https://openalex.org/W2396274919","https://openalex.org/W2411412724","https://openalex.org/W2745859992","https://openalex.org/W4230766380","https://openalex.org/W6668990524","https://openalex.org/W6677871018","https://openalex.org/W6682324061","https://openalex.org/W6693066272","https://openalex.org/W6742827162"],"related_works":["https://openalex.org/W2998370018","https://openalex.org/W3125052734","https://openalex.org/W3123982513","https://openalex.org/W4391249506","https://openalex.org/W2951795132","https://openalex.org/W2755286209","https://openalex.org/W4312092966","https://openalex.org/W2970345194","https://openalex.org/W2161240633","https://openalex.org/W4386821976"],"abstract_inverted_index":{"The":[0,143],"fusion":[1,53,76,188],"of":[2,22,26,50,77,96,120,197],"vision":[3,14],"and":[4,12,40,43,81,88,94,109,138,164,175,186,199],"inertial":[5],"data":[6,107,166],"become":[7],"very":[8],"popular":[9],"in":[10,46,195],"robotics":[11],"computer":[13],"community":[15],"presently":[16],"due":[17],"to":[18,33,83,90,116,127],"the":[19,23,51,59,75,85,92,97,106,118,121,129,151,154,165,176,182,190],"complementary":[20],"nature":[21],"two":[24],"kind":[25],"sensing":[27],"modalities,":[28],"which":[29,62,149],"can":[30],"be":[31],"exploited":[32,126],"many":[34],"applications,":[35],"such":[36,132],"as":[37,133],"VR,":[38],"3D":[39],"simultaneous":[41],"localization":[42],"mapping":[44],"(SLAM)":[45],"robotics.":[47],"But":[48],"most":[49],"proposed":[52,191],"methods":[54],"are":[55,125,172],"implemented":[56],"based":[57,140],"on":[58],"filtering":[60],"schemes,":[61],"make":[63],"it":[64],"unsuitable":[65],"for":[66,105,153],"large":[67],"scale":[68],"environment.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73],"apply":[74],"a":[78,110],"stereovision":[79],"system":[80],"IMU":[82],"address":[84],"SLAM":[86],"issues,":[87],"aim":[89],"improve":[91],"accuracy":[93,198],"robustness":[95],"results.":[98],"A":[99],"tightly":[100],"coupled":[101],"framework":[102],"is":[103,114,147,193],"adopted":[104],"association":[108],"non-linear":[111,156],"optimization":[112],"backend":[113,155],"used":[115],"enhance":[117],"consistency":[119],"map.":[122],"Some":[123,158],"strategies":[124],"reduce":[128],"computational":[130],"complexity,":[131],"pre-integration":[134],"method,":[135],"QR":[136],"decomposition":[137],"key-frame":[139],"feature":[141],"extraction.":[142],"DBoW-based":[144],"loop-closure":[145],"detection":[146],"integrated":[148],"provides":[150],"constraints":[152],"optimization.":[157],"experiments":[159],"with":[160,181],"open":[161],"source":[162],"dataset":[163],"collected":[167],"by":[168],"our":[169],"intelligent":[170],"vehicle":[171],"carried":[173],"out":[174],"results":[177],"show":[178],"that,":[179],"compared":[180],"existing":[183],"monocular":[184],"VINS":[185],"open-loop":[187],"methods,":[189],"approach":[192],"outperformed":[194],"terms":[196],"robustness.":[200]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
