{"id":"https://openalex.org/W3207897722","doi":"https://doi.org/10.1109/icra48506.2021.9561353","title":"Efficient Map Prediction via Low-Rank Matrix Completion","display_name":"Efficient Map Prediction via Low-Rank Matrix Completion","publication_year":2021,"publication_date":"2021-05-30","ids":{"openalex":"https://openalex.org/W3207897722","doi":"https://doi.org/10.1109/icra48506.2021.9561353","mag":"3207897722"},"language":"en","primary_location":{"id":"doi:10.1109/icra48506.2021.9561353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","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/A5100370637","display_name":"Zheng Chen","orcid":"https://orcid.org/0000-0001-7032-4826"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zheng Chen","raw_affiliation_strings":["Luddy School of Informatics, Computing, and Engineering at Indiana University, Bloomington, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Luddy School of Informatics, Computing, and Engineering at Indiana University, Bloomington, IN, USA","institution_ids":["https://openalex.org/I4210119109"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101562163","display_name":"Shi Bai","orcid":"https://orcid.org/0000-0002-6081-3084"},"institutions":[{"id":"https://openalex.org/I4210128969","display_name":"Alphabet (United States)","ror":"https://ror.org/02e9yx751","country_code":"US","type":"company","lineage":["https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shi Bai","raw_affiliation_strings":["Wing, Alphabet Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wing, Alphabet Inc","institution_ids":["https://openalex.org/I4210128969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101917996","display_name":"Lantao Liu","orcid":"https://orcid.org/0000-0002-6796-6817"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lantao Liu","raw_affiliation_strings":["Luddy School of Informatics, Computing, and Engineering at Indiana University, Bloomington, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Luddy School of Informatics, Computing, and Engineering at Indiana University, Bloomington, IN, USA","institution_ids":["https://openalex.org/I4210119109"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5981,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78139472,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"13953","last_page":"13959"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9944999814033508,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9916999936103821,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7194496393203735},{"id":"https://openalex.org/keywords/extrapolation","display_name":"Extrapolation","score":0.6670995950698853},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.6333106160163879},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6000517010688782},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5934498310089111},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48701173067092896},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.482827752828598},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4669450521469116},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4639403820037842},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.44561222195625305},{"id":"https://openalex.org/keywords/map-matching","display_name":"Map matching","score":0.4173988103866577},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.411824494600296},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.382082462310791},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17964494228363037},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0836227536201477}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7194496393203735},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.6670995950698853},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.6333106160163879},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6000517010688782},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5934498310089111},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48701173067092896},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.482827752828598},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4669450521469116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4639403820037842},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.44561222195625305},{"id":"https://openalex.org/C2778559875","wikidata":"https://www.wikidata.org/wiki/Q1892023","display_name":"Map matching","level":3,"score":0.4173988103866577},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.411824494600296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.382082462310791},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17964494228363037},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0836227536201477},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48506.2021.9561353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1604604340","https://openalex.org/W1977189000","https://openalex.org/W1998635907","https://openalex.org/W1999050017","https://openalex.org/W2013229266","https://openalex.org/W2020152488","https://openalex.org/W2059283452","https://openalex.org/W2103972604","https://openalex.org/W2118425803","https://openalex.org/W2120872934","https://openalex.org/W2134332047","https://openalex.org/W2144002138","https://openalex.org/W2146130798","https://openalex.org/W2166163936","https://openalex.org/W2171046470","https://openalex.org/W2198547365","https://openalex.org/W2291737362","https://openalex.org/W2410641873","https://openalex.org/W2508520405","https://openalex.org/W2510569111","https://openalex.org/W2562555892","https://openalex.org/W2569527682","https://openalex.org/W2611328865","https://openalex.org/W2613579343","https://openalex.org/W2751391930","https://openalex.org/W2771211602","https://openalex.org/W2790223694","https://openalex.org/W2794331967","https://openalex.org/W2957946950","https://openalex.org/W2959972908","https://openalex.org/W2962976886","https://openalex.org/W2963375846","https://openalex.org/W2963705450","https://openalex.org/W2964664157","https://openalex.org/W2967029387","https://openalex.org/W2967657713","https://openalex.org/W2968968404","https://openalex.org/W3003365835","https://openalex.org/W3004346718","https://openalex.org/W3010434925","https://openalex.org/W3015031642","https://openalex.org/W3099447760","https://openalex.org/W3104062571","https://openalex.org/W3104501706","https://openalex.org/W3129392366","https://openalex.org/W3130186063","https://openalex.org/W3186014234","https://openalex.org/W4300657658","https://openalex.org/W6636014196","https://openalex.org/W6636904114","https://openalex.org/W6677493787","https://openalex.org/W6677959539","https://openalex.org/W6682042988","https://openalex.org/W6686567431","https://openalex.org/W6744287318","https://openalex.org/W6746047595","https://openalex.org/W6749522230","https://openalex.org/W6750520372","https://openalex.org/W6790578863"],"related_works":["https://openalex.org/W2168645698","https://openalex.org/W2560420848","https://openalex.org/W2167211785","https://openalex.org/W2052829037","https://openalex.org/W4237321385","https://openalex.org/W2163053068","https://openalex.org/W4233216102","https://openalex.org/W3144354057","https://openalex.org/W2788210652","https://openalex.org/W2972830027"],"abstract_inverted_index":{"In":[0],"many":[1],"autonomous":[2],"mapping":[3,93],"tasks,":[4],"the":[5,67,77,103,109],"maps":[6,54],"cannot":[7],"be":[8,133],"accurately":[9],"constructed":[10],"due":[11],"to":[12,44,81],"various":[13],"reasons":[14],"such":[15],"as":[16],"sparse,":[17],"noisy,":[18],"and":[19,49,76,95,129],"partial":[20],"sensor":[21],"measurements.":[22],"We":[23,60],"propose":[24],"a":[25,117],"novel":[26],"map":[27,40,47,83,106],"prediction":[28,41,84,107],"method":[29],"built":[30],"upon":[31],"recent":[32],"success":[33],"of":[34,92,119],"Low-Rank":[35],"Matrix":[36],"Completion.":[37],"The":[38],"proposed":[39,104],"is":[42,79],"able":[43],"achieve":[45,70],"both":[46],"interpolation":[48],"extrapolation":[50],"on":[51],"raw":[52],"poor-quality":[53],"with":[55,62,102],"missing":[56],"or":[57],"noisy":[58],"observations.":[59],"validate":[61],"extensive":[63],"simulated":[64],"experiments":[65],"that":[66,101],"approach":[68,85],"can":[69,132],"real-time":[71,105],"computation":[72,96],"for":[73,116,126],"large":[74],"maps,":[75],"performance":[78],"superior":[80],"state-of-the-art":[82],"\u2014":[86],"Bayesian":[87],"Hilbert":[88],"Mapping":[89],"in":[90],"terms":[91],"accuracy":[94],"time.":[97],"Then":[98],"we":[99],"demonstrate":[100],"framework,":[108],"coverage":[110,121],"convergence":[111],"rate":[112],"(per":[113],"action":[114],"step)":[115],"set":[118],"representative":[120],"planning":[122],"methods":[123],"commonly":[124],"used":[125],"environmental":[127],"modeling":[128],"monitoring":[130],"tasks":[131],"significantly":[134],"improved.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
