{"id":"https://openalex.org/W3005121652","doi":"https://doi.org/10.1109/icar46387.2019.8981570","title":"BooM-Vio: Bootstrapped Monocular Visual-Inertial Odometry with Absolute Trajectory Estimation through Unsupervised Deep Learning","display_name":"BooM-Vio: Bootstrapped Monocular Visual-Inertial Odometry with Absolute Trajectory Estimation through Unsupervised Deep Learning","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3005121652","doi":"https://doi.org/10.1109/icar46387.2019.8981570","mag":"3005121652"},"language":"en","primary_location":{"id":"doi:10.1109/icar46387.2019.8981570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icar46387.2019.8981570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 19th International Conference on Advanced Robotics (ICAR)","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/A5073480368","display_name":"Kyle Lindgren","orcid":"https://orcid.org/0000-0002-8216-074X"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kyle Lindgren","raw_affiliation_strings":["Dept. of Electrical Engineering, University of Washington, 185 Stevens Way, Paul Allen Center, Room AE100R, Campus Box 352500, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, University of Washington, 185 Stevens Way, Paul Allen Center, Room AE100R, Campus Box 352500, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112366606","display_name":"Sarah Leung","orcid":null},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sarah Leung","raw_affiliation_strings":["US Army Research Laboratory, Adelphi, MD, USA"],"affiliations":[{"raw_affiliation_string":"US Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112601078","display_name":"William D. Nothwang","orcid":null},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William D. Nothwang","raw_affiliation_strings":["US Army Research Laboratory, Adelphi, MD, USA"],"affiliations":[{"raw_affiliation_string":"US Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046529553","display_name":"E. Jared Shamwell","orcid":"https://orcid.org/0000-0002-7991-6454"},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"E. Jared Shamwell","raw_affiliation_strings":["US Army Research Laboratory, Adelphi, MD, USA"],"affiliations":[{"raw_affiliation_string":"US Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073480368"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.7934,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81617961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"516","last_page":"522"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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":1.0,"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":0.9998999834060669,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.8021891117095947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7894291877746582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7438656091690063},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.7330170273780823},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6881662011146545},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6325051784515381},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.6275525093078613},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.583940327167511},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.5333495140075684},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.46059027314186096},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4179065525531769},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.2594173848628998},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.18422815203666687}],"concepts":[{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.8021891117095947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7894291877746582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7438656091690063},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.7330170273780823},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6881662011146545},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6325051784515381},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.6275525093078613},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.583940327167511},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.5333495140075684},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.46059027314186096},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4179065525531769},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2594173848628998},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.18422815203666687},{"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},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icar46387.2019.8981570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icar46387.2019.8981570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 19th International Conference on Advanced Robotics (ICAR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W1612997784","https://openalex.org/W1970504153","https://openalex.org/W2091790851","https://openalex.org/W2108134361","https://openalex.org/W2115579991","https://openalex.org/W2118223742","https://openalex.org/W2150066425","https://openalex.org/W2151290401","https://openalex.org/W2170282673","https://openalex.org/W2300779272","https://openalex.org/W2520707372","https://openalex.org/W2559203616","https://openalex.org/W2609883120","https://openalex.org/W2615547864","https://openalex.org/W2745859992","https://openalex.org/W2754177129","https://openalex.org/W2754329383","https://openalex.org/W2909157769","https://openalex.org/W2945356051","https://openalex.org/W2952348863","https://openalex.org/W2962816904","https://openalex.org/W2962867206","https://openalex.org/W2964314455","https://openalex.org/W3099788636","https://openalex.org/W3103648783","https://openalex.org/W6618372016","https://openalex.org/W6697658144","https://openalex.org/W6730329805"],"related_works":["https://openalex.org/W2979950214","https://openalex.org/W87609089","https://openalex.org/W3024737167","https://openalex.org/W2998370018","https://openalex.org/W2414561716","https://openalex.org/W3161199934","https://openalex.org/W2303855011","https://openalex.org/W3125052734","https://openalex.org/W3123982513","https://openalex.org/W2312326526"],"abstract_inverted_index":{"Machine":[0],"learning":[1],"has":[2],"emerged":[3],"as":[4,143,145],"an":[5],"extraordinary":[6],"tool":[7],"for":[8],"solving":[9],"many":[10,43],"computer":[11],"vision":[12],"tasks":[13],"by":[14],"extracting":[15],"and":[16,108],"correlating":[17],"meaningful":[18],"features":[19],"from":[20,121,126],"high":[21],"dimensional":[22],"inputs":[23],"in":[24,155],"ways":[25],"that":[26,75,152],"often":[27,54],"exceed":[28],"the":[29,35,77,86,139,156,163],"best":[30],"human-derived":[31],"modeling":[32],"efforts.":[33],"However,":[34],"area":[36],"of":[37,82,165],"vision-aided":[38],"localization":[39],"remains":[40],"diverse":[41],"with":[42,85,93],"traditional,":[44],"model-based":[45,94],"approaches":[46,84],"(i.e.":[47],"filtering-":[48],"or":[49],"nonlinear":[50],"least-":[51],"squares-":[52],"based)":[53],"outperforming":[55],"deep,":[56],"model-free":[57,83],"approaches.":[58,95],"In":[59],"this":[60],"work,":[61],"we":[62,153],"present":[63],"Bootstrapped":[64],"Monocular":[65],"VIO":[66],"(BooM),":[67],"a":[68,117,134,146],"scaled":[69],"monocular":[70],"visual-inertial":[71,106],"odometry":[72,107],"(VIO)":[73],"solution":[74],"leverages":[76],"complex":[78],"data":[79],"association":[80],"ability":[81,87],"to":[88,104],"exploit":[89],"known":[90],"geometric":[91],"dynamics":[92],"Our":[96],"end-to-end,":[97],"unsupervised":[98],"deep":[99],"neural":[100],"network":[101,132],"simultaneously":[102],"learns":[103],"perform":[105],"estimate":[109],"scene":[110],"depth":[111],"while":[112],"scale":[113],"is":[114],"enforced":[115],"through":[116,169],"loss":[118],"signal":[119],"computed":[120],"position":[122],"change":[123],"magnitude":[124],"estimates":[125],"traditional":[127],"methods.":[128],"We":[129,160],"evaluate":[130],"our":[131,166],"against":[133],"state-of-the-art":[135],"(SoA)":[136],"approach":[137,168],"on":[138,172],"KITTI":[140],"driving":[141],"dataset":[142,151],"well":[144],"micro":[147],"aerial":[148],"vehicle":[149],"(MAV)":[150],"collected":[154],"AirSim":[157],"simulation":[158],"environment.":[159],"further":[161],"demonstrate":[162],"benefits":[164],"combined":[167],"robustness":[170],"tests":[171],"degraded":[173],"trajectories.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}