{"id":"https://openalex.org/W4294690659","doi":"https://doi.org/10.23919/acc53348.2022.9867354","title":"Target Tracking with Frame- and Event-based Cameras Involving Delayed and Irregularly-Sampled Visual Feedback for a Robotic Air-Hockey System","display_name":"Target Tracking with Frame- and Event-based Cameras Involving Delayed and Irregularly-Sampled Visual Feedback for a Robotic Air-Hockey System","publication_year":2022,"publication_date":"2022-06-08","ids":{"openalex":"https://openalex.org/W4294690659","doi":"https://doi.org/10.23919/acc53348.2022.9867354"},"language":"en","primary_location":{"id":"doi:10.23919/acc53348.2022.9867354","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc53348.2022.9867354","pdf_url":null,"source":{"id":"https://openalex.org/S4363607732","display_name":"2022 American Control Conference (ACC)","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 American Control Conference (ACC)","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/A5101860563","display_name":"Hui Xiao","orcid":"https://orcid.org/0000-0003-1136-5702"},"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":"Hui Xiao","raw_affiliation_strings":["University of Washington,Department of Mechanical Engineering,Seattle,WA,USA,98195"],"affiliations":[{"raw_affiliation_string":"University of Washington,Department of Mechanical Engineering,Seattle,WA,USA,98195","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041455132","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0003-1252-2087"},"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":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["University of Washington,Department of Mechanical Engineering,Seattle,WA,USA,98195"],"affiliations":[{"raw_affiliation_string":"University of Washington,Department of Mechanical Engineering,Seattle,WA,USA,98195","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101860563"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08807369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3771","last_page":"3776"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11236","display_name":"Control Systems and Identification","score":0.9872000217437744,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9840999841690063,"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/kalman-filter","display_name":"Kalman filter","score":0.7590548992156982},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6745502352714539},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6737037897109985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6621930003166199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.626556932926178},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5955637693405151},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5560170412063599},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.48677778244018555},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.46012282371520996},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3701080083847046},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.36587145924568176},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.1878141462802887}],"concepts":[{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7590548992156982},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6745502352714539},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6737037897109985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6621930003166199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.626556932926178},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5955637693405151},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5560170412063599},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.48677778244018555},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.46012282371520996},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3701080083847046},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.36587145924568176},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.1878141462802887},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"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:10.23919/acc53348.2022.9867354","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc53348.2022.9867354","pdf_url":null,"source":{"id":"https://openalex.org/S4363607732","display_name":"2022 American Control Conference (ACC)","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 American Control Conference (ACC)","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":12,"referenced_works":["https://openalex.org/W1597922605","https://openalex.org/W1805947143","https://openalex.org/W2003219976","https://openalex.org/W2020968226","https://openalex.org/W2041307253","https://openalex.org/W2113391017","https://openalex.org/W2238582461","https://openalex.org/W2502893273","https://openalex.org/W2592723677","https://openalex.org/W2999153562","https://openalex.org/W3040838455","https://openalex.org/W6638496609"],"related_works":["https://openalex.org/W2394134009","https://openalex.org/W1971984615","https://openalex.org/W2046099857","https://openalex.org/W2806679586","https://openalex.org/W4315836311","https://openalex.org/W2393252924","https://openalex.org/W2318603563","https://openalex.org/W2787600244","https://openalex.org/W4285271403","https://openalex.org/W2091015105"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,7,62,87],"target":[3],"tracking":[4,122,127,140],"system":[5],"for":[6,65,78],"robotic":[8],"air-hockey":[9],"player,":[10],"where":[11],"the":[12,15,32,36,40,42,46,51,59,83,111,135,138],"state":[13],"of":[14,35,45,58,137],"puck":[16,84],"is":[17,48,75,92,129],"optimally":[18],"estimated":[19],"by":[20,50],"fusing":[21],"measurements":[22,60],"from":[23,120],"frame-":[24],"and":[25,54,98,107],"event-based":[26],"vision":[27],"sensors.":[28],"In":[29],"addition":[30],"to":[31,94,115,123],"jumping":[33],"velocity":[34],"tracked":[37],"object":[38],"during":[39],"game,":[41],"technical":[43],"challenge":[44,64],"problem":[47],"amplified":[49],"variable":[52],"delay":[53],"irregular":[55],"sampling":[56],"intervals":[57],"\u2014":[61],"thematic":[63],"controls":[66],"under":[67],"such":[68],"visual":[69],"feedback.":[70],"An":[71],"auto-restart":[72,89],"Kalman":[73,90],"filter":[74,91],"first":[76],"proposed":[77,112,139],"compensating":[79],"sudden":[80],"jumps":[81],"in":[82,131],"state.":[85],"Then":[86],"memory-enabled":[88],"derived":[93],"additionally":[95],"accommodate":[96],"delays":[97],"sensing":[99],"irregularities.":[100],"Building":[101],"on":[102],"physics-based":[103],"modeling,":[104],"model-based":[105],"filtering,":[106],"mixed":[108],"sensor":[109],"management,":[110],"method":[113],"applies":[114],"other":[116],"vision-based":[117],"control":[118],"systems":[119],"motion":[121],"manufacturing":[124],"automation.":[125],"The":[126],"performance":[128],"analyzed":[130],"simulation":[132],"that":[133],"shows":[134],"effectiveness":[136],"algorithm.":[141]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}