{"id":"https://openalex.org/W4387090080","doi":"https://doi.org/10.1109/ecmr59166.2023.10256296","title":"Learning State-Space Models for Mapping Spatial Motion Patterns","display_name":"Learning State-Space Models for Mapping Spatial Motion Patterns","publication_year":2023,"publication_date":"2023-09-04","ids":{"openalex":"https://openalex.org/W4387090080","doi":"https://doi.org/10.1109/ecmr59166.2023.10256296"},"language":"en","primary_location":{"id":"doi:10.1109/ecmr59166.2023.10256296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecmr59166.2023.10256296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 European Conference on Mobile Robots (ECMR)","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/A5036233277","display_name":"Junyi Shi","orcid":"https://orcid.org/0000-0001-6465-1396"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Junyi Shi","raw_affiliation_strings":["Aalto University,Department of Electrical Engineering and Automation,Finland","Department of Electrical Engineering and Automation, Aalto University, Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University,Department of Electrical Engineering and Automation,Finland","institution_ids":["https://openalex.org/I9927081"]},{"raw_affiliation_string":"Department of Electrical Engineering and Automation, Aalto University, Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086791812","display_name":"Tomasz Piotr Kucner","orcid":"https://orcid.org/0000-0002-9503-0602"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Tomasz Piotr Kucner","raw_affiliation_strings":["Aalto University,Department of Electrical Engineering and Automation,Finland","Finnish Center of Artificial Intelligence, Finland","Department of Electrical Engineering and Automation, Aalto University, Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University,Department of Electrical Engineering and Automation,Finland","institution_ids":["https://openalex.org/I9927081"]},{"raw_affiliation_string":"Finnish Center of Artificial Intelligence, Finland","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical Engineering and Automation, Aalto University, Finland","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036233277"],"corresponding_institution_ids":["https://openalex.org/I9927081"],"apc_list":null,"apc_paid":null,"fwci":0.345,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57497945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9970999956130981,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9961000084877014,"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":0.7838823199272156},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.722611665725708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7015663385391235},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6452969312667847},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.5953836441040039},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5325813293457031},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4999661445617676},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4751793444156647},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.44482970237731934},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.4408075213432312},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11977863311767578}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7838823199272156},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.722611665725708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7015663385391235},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6452969312667847},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.5953836441040039},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5325813293457031},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4999661445617676},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4751793444156647},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.44482970237731934},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.4408075213432312},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11977863311767578},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ecmr59166.2023.10256296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecmr59166.2023.10256296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 European Conference on Mobile Robots (ECMR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307957","display_name":"Volkswagen of America","ror":"https://ror.org/034e5n787"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1033316025","https://openalex.org/W1558470758","https://openalex.org/W1780392298","https://openalex.org/W1924770834","https://openalex.org/W1959608418","https://openalex.org/W1979223226","https://openalex.org/W2037629065","https://openalex.org/W2045182214","https://openalex.org/W2077638917","https://openalex.org/W2124202837","https://openalex.org/W2133844819","https://openalex.org/W2135261438","https://openalex.org/W2145647377","https://openalex.org/W2150879893","https://openalex.org/W2154418813","https://openalex.org/W2580991611","https://openalex.org/W2894495332","https://openalex.org/W2908510526","https://openalex.org/W2963001155","https://openalex.org/W3003257820","https://openalex.org/W3033920763","https://openalex.org/W3106257603","https://openalex.org/W3130950696","https://openalex.org/W3201337335","https://openalex.org/W3208821282","https://openalex.org/W4232464081","https://openalex.org/W4237840503","https://openalex.org/W4289294484","https://openalex.org/W4293253009","https://openalex.org/W4295312788","https://openalex.org/W4308128926","https://openalex.org/W4385245566","https://openalex.org/W6640212811","https://openalex.org/W6640963894","https://openalex.org/W6756256016","https://openalex.org/W6757817989","https://openalex.org/W6766978945","https://openalex.org/W6779433390","https://openalex.org/W6842253040","https://openalex.org/W7072098258"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W1904098742","https://openalex.org/W3158921809","https://openalex.org/W2161428574","https://openalex.org/W2077416514","https://openalex.org/W2618632915","https://openalex.org/W4292862729","https://openalex.org/W2150982344","https://openalex.org/W2157678966"],"abstract_inverted_index":{"Mapping":[0],"the":[1,7,25,31,65,106,132,138],"surrounding":[2],"environment":[3,26],"is":[4,27],"essential":[5],"for":[6],"successful":[8],"operation":[9],"of":[10,33,68,108],"autonomous":[11],"robots.":[12],"While":[13],"extensive":[14],"research":[15],"has":[16,137],"focused":[17],"on":[18],"mapping":[19,116],"geometric":[20],"structures":[21],"and":[22,48,72,98,118,136],"static":[23],"objects,":[24],"also":[28],"influenced":[29],"by":[30,111],"movement":[32],"dynamic":[34],"objects.":[35],"Incorporating":[36],"information":[37],"about":[38],"spatial":[39,69],"motion":[40,70,96,134],"patterns":[41,71,97],"can":[42,129],"allow":[43],"mobile":[44],"robots":[45],"to":[46,120,140,143],"navigate":[47],"operate":[49],"successfully":[50],"in":[51],"populated":[52],"areas.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57,86],"propose":[58],"a":[59,79],"deep":[60],"state-space":[61],"model":[62,110,128],"that":[63,126],"learns":[64],"map":[66],"representations":[67],"how":[73],"they":[74],"change":[75],"over":[76],"time":[77],"at":[78],"certain":[80],"place.":[81],"To":[82],"evaluate":[83],"our":[84,109,127],"methods,":[85],"use":[87],"two":[88],"different":[89],"datasets:":[90],"one":[91],"generated":[92],"dataset":[93],"with":[94,100],"specific":[95],"another":[99],"real-world":[101],"pedestrian":[102],"data.":[103],"We":[104],"test":[105],"performance":[107],"evaluating":[112],"its":[113],"learning":[114],"ability,":[115],"quality,":[117],"application":[119,145],"downstream":[121],"tasks.":[122,146],"The":[123],"results":[124],"demonstrate":[125],"effectively":[130],"learn":[131],"corresponding":[133],"pattern,":[135],"potential":[139],"be":[141],"applied":[142],"robotic":[144]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
