{"id":"https://openalex.org/W4221147664","doi":"https://doi.org/10.48550/arxiv.2203.03959","title":"Enhancing Door-Status Detection for Autonomous Mobile Robots during Environment-Specific Operational Use","display_name":"Enhancing Door-Status Detection for Autonomous Mobile Robots during Environment-Specific Operational Use","publication_year":2022,"publication_date":"2022-03-08","ids":{"openalex":"https://openalex.org/W4221147664","doi":"https://doi.org/10.48550/arxiv.2203.03959"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2203.03959","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.03959","pdf_url":"https://arxiv.org/pdf/2203.03959","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2203.03959","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052452333","display_name":"Michele Antonazzi","orcid":"https://orcid.org/0000-0001-6396-7567"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Antonazzi, Michele","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020142519","display_name":"Matteo Luperto","orcid":"https://orcid.org/0000-0002-8976-2073"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luperto, Matteo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090235510","display_name":"Nicola Basilico","orcid":"https://orcid.org/0000-0002-4512-3480"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Basilico, Nicola","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001947622","display_name":"N. Alberto Borghese","orcid":"https://orcid.org/0000-0002-0925-3448"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Borghese, N. Alberto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9979000091552734,"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":0.9969000220298767,"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/T12288","display_name":"Optimization and Search Problems","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/leverage","display_name":"Leverage (statistics)","score":0.8064696192741394},{"id":"https://openalex.org/keywords/doors","display_name":"Doors","score":0.7657581567764282},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.7061197757720947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6873865723609924},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6618684530258179},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5973179936408997},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5774744153022766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.523565948009491},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4883872866630554},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4375993609428406},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4108033776283264},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3778136968612671},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3340660631656647},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33054250478744507},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1896113157272339},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.09620407223701477},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07699427008628845}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.8064696192741394},{"id":"https://openalex.org/C125209513","wikidata":"https://www.wikidata.org/wiki/Q4037520","display_name":"Doors","level":2,"score":0.7657581567764282},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.7061197757720947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6873865723609924},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6618684530258179},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5973179936408997},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5774744153022766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.523565948009491},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4883872866630554},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4375993609428406},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4108033776283264},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3778136968612671},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3340660631656647},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33054250478744507},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1896113157272339},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.09620407223701477},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07699427008628845}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2203.03959","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.03959","pdf_url":"https://arxiv.org/pdf/2203.03959","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2203.03959","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2203.03959","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2203.03959","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.03959","pdf_url":"https://arxiv.org/pdf/2203.03959","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1033316025","https://openalex.org/W1567193306","https://openalex.org/W1861492603","https://openalex.org/W1992083653","https://openalex.org/W1994956562","https://openalex.org/W2031489346","https://openalex.org/W2086724557","https://openalex.org/W2113321439","https://openalex.org/W2115924296","https://openalex.org/W2126791158","https://openalex.org/W2167340365","https://openalex.org/W2194775991","https://openalex.org/W2402652555","https://openalex.org/W2410369356","https://openalex.org/W2626895984","https://openalex.org/W2794284562","https://openalex.org/W2963037989","https://openalex.org/W2963733582","https://openalex.org/W2964248288","https://openalex.org/W2964339842","https://openalex.org/W3091442961","https://openalex.org/W3096609285","https://openalex.org/W3150631816","https://openalex.org/W3159782171","https://openalex.org/W4239072543","https://openalex.org/W4281746058","https://openalex.org/W4293584584","https://openalex.org/W4294310790","https://openalex.org/W4297182666","https://openalex.org/W4307863552","https://openalex.org/W4310605739","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W3016239942","https://openalex.org/W2486091485","https://openalex.org/W4293365988","https://openalex.org/W2374188760","https://openalex.org/W2997934945","https://openalex.org/W2468876127","https://openalex.org/W4205206412","https://openalex.org/W2885750329","https://openalex.org/W2487340859","https://openalex.org/W2963610131"],"abstract_inverted_index":{"Door-status":[0],"detection,":[1],"namely":[2],"recognizing":[3],"the":[4,38,41,48,62,71,87,96,137,146,153,165,178,190],"presence":[5],"of":[6,40,50,74,79,101,114,141,167,189],"a":[7,17,21,52,57,66,102,108,112,118,127,142,183],"door":[8],"and":[9,121,176,187],"its":[10,150],"status":[11],"(open":[12],"or":[13,34],"closed),":[14],"can":[15,32],"induce":[16],"remarkable":[18],"impact":[19],"on":[20,91,131],"mobile":[22,58,103],"robot's":[23,119],"navigation":[24],"performance,":[25],"especially":[26],"for":[27,56,65,148],"dynamic":[28],"settings":[29],"where":[30],"doors":[31,75],"enable":[33],"disable":[35],"passages,":[36],"changing":[37],"topology":[39],"map.":[42],"In":[43],"this":[44,168],"work,":[45],"we":[46,82,106,122],"address":[47],"problem":[49],"building":[51],"door-status":[53,128],"detector":[54,129],"module":[55],"robot":[59,143],"operating":[60],"in":[61,152,174,177],"same":[63,72],"environment":[64,155],"long":[67],"time,":[68],"thus":[69],"observing":[70],"set":[73],"from":[76,117],"different":[77],"points":[78],"view.":[80],"First,":[81],"show":[83],"how":[84],"to":[85,110,125,144],"improve":[86],"mainstream":[88],"approach":[89],"based":[90,130],"object":[92],"detection":[93],"by":[94],"considering":[95],"constrained":[97],"perception":[98],"setup":[99],"typical":[100,138],"robot.":[104],"Hence,":[105],"devise":[107],"method":[109,169],"build":[111],"dataset":[113],"images":[115],"taken":[116],"perspective":[120],"exploit":[123],"it":[124],"obtain":[126],"deep":[132],"learning.":[133],"We":[134],"then":[135],"leverage":[136],"working":[139,154],"conditions":[140],"qualify":[145],"model":[147],"boosting":[149],"performance":[151],"via":[156],"fine-tuning":[157,191],"with":[158,170],"additional":[159],"data.":[160],"Our":[161],"experimental":[162],"analysis":[163],"shows":[164],"effectiveness":[166],"results":[171],"obtained":[172],"both":[173],"simulation":[175],"real-world,":[179],"that":[180],"also":[181],"highlight":[182],"trade-off":[184],"between":[185],"costs":[186],"benefits":[188],"approach.":[192]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}