{"id":"https://openalex.org/W4206138072","doi":"https://doi.org/10.1109/lra.2022.3141661","title":"Multi-Robot Collaborative Perception With Graph Neural Networks","display_name":"Multi-Robot Collaborative Perception With Graph Neural Networks","publication_year":2022,"publication_date":"2022-01-10","ids":{"openalex":"https://openalex.org/W4206138072","doi":"https://doi.org/10.1109/lra.2022.3141661"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2022.3141661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3141661","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2201.01760","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062796058","display_name":"Yang Zhou","orcid":"https://orcid.org/0000-0002-2001-427X"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yang Zhou","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033664308","display_name":"Jiuhong Xiao","orcid":"https://orcid.org/0000-0002-7574-398X"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiuhong Xiao","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101804737","display_name":"Yue Zhou","orcid":"https://orcid.org/0000-0003-1765-8629"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Zhou","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077485450","display_name":"Giuseppe Loianno","orcid":"https://orcid.org/0000-0002-3263-5401"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Giuseppe Loianno","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5062796058"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":52.2002,"has_fulltext":false,"cited_by_count":94,"citation_normalized_percentile":{"value":0.9987008,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"7","issue":"2","first_page":"2289","last_page":"2296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9991000294685364,"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":0.9991000294685364,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5876175165176392},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5620312094688416},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.48238077759742737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4488818049430847},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44770270586013794},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42862528562545776},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.35245072841644287},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34540989995002747},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.16288939118385315},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14726907014846802}],"concepts":[{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5876175165176392},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5620312094688416},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.48238077759742737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4488818049430847},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44770270586013794},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42862528562545776},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.35245072841644287},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34540989995002747},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.16288939118385315},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14726907014846802}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lra.2022.3141661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3141661","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2201.01760","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.01760","pdf_url":"https://arxiv.org/pdf/2201.01760","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2201.01760","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.01760","pdf_url":"https://arxiv.org/pdf/2201.01760","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":46,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2116341502","https://openalex.org/W2412782625","https://openalex.org/W2557430988","https://openalex.org/W2604314403","https://openalex.org/W2760103357","https://openalex.org/W2949924544","https://openalex.org/W2951234442","https://openalex.org/W2963163009","https://openalex.org/W2964015378","https://openalex.org/W2972980981","https://openalex.org/W2985775862","https://openalex.org/W3028801376","https://openalex.org/W3034180589","https://openalex.org/W3035098634","https://openalex.org/W3035397262","https://openalex.org/W3035541121","https://openalex.org/W3080555959","https://openalex.org/W3082697078","https://openalex.org/W3090375251","https://openalex.org/W3092774272","https://openalex.org/W3118885154","https://openalex.org/W3119954594","https://openalex.org/W3130631955","https://openalex.org/W3136230454","https://openalex.org/W3138885497","https://openalex.org/W3166401044","https://openalex.org/W3205996514","https://openalex.org/W4285723986","https://openalex.org/W4288404646","https://openalex.org/W4294558607","https://openalex.org/W4295312788","https://openalex.org/W6639824700","https://openalex.org/W6685261749","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6740674931","https://openalex.org/W6757555829","https://openalex.org/W6760725535","https://openalex.org/W6766978945","https://openalex.org/W6779084649","https://openalex.org/W6781932242","https://openalex.org/W6782364735","https://openalex.org/W6791807693"],"related_works":["https://openalex.org/W2628861693","https://openalex.org/W8302103","https://openalex.org/W3203087560","https://openalex.org/W4361279463","https://openalex.org/W3171631314","https://openalex.org/W2674584172","https://openalex.org/W2391251536","https://openalex.org/W2967743314","https://openalex.org/W2606825221","https://openalex.org/W4392646554"],"abstract_inverted_index":{"Multi-robot":[0],"systems":[1,43],"such":[2,120],"as":[3,99,101,121],"swarms":[4],"of":[5,145],"aerial":[6,139],"robots":[7],"are":[8],"naturally":[9],"suited":[10],"to":[11,22,45,50,61,68,88,103],"offer":[12],"additional":[13],"flexibility,":[14],"resilience,":[15],"and":[16,39,53,106,125,133,159],"robustness":[17],"in":[18,90,149],"several":[19],"tasks":[20],"compared":[21],"a":[23,78],"single":[24,94],"robot":[25,36],"by":[26,156],"enabling":[27],"cooperation":[28],"among":[29,57],"the":[30,34,58,85,111,143,146],"agents.":[31],"To":[32],"enhance":[33],"autonomous":[35],"decision-making":[37],"process":[38],"situational":[40],"awareness,":[41],"multi-robot":[42,91],"have":[44],"coordinate":[46],"their":[47],"perception":[48,92,97,118],"capabilities":[49],"collect,":[51],"share,":[52],"fuse":[54],"environment":[55],"information":[56,64],"agents":[59],"efficiently":[60],"obtain":[62],"context-appropriate":[63],"or":[65,71,162],"gain":[66],"resilience":[67,102],"sensor":[69,104],"noise":[70,158],"failures.":[72,163],"In":[73],"this":[74],"letter,":[75],"we":[76],"propose":[77],"general-purpose":[79],"Graph":[80],"Neural":[81],"Network":[82],"(GNN)":[83],"with":[84],"main":[86],"goal":[87],"increase,":[89],"tasks,":[93],"robots&#x2019;":[95,140],"inference":[96,151],"accuracy":[98],"well":[100],"failures":[105],"disturbances.":[107],"We":[108],"show":[109,142],"that":[110],"proposed":[112,147],"framework":[113],"can":[114],"address":[115],"multi-view":[116],"visual":[117],"problems":[119],"monocular":[122],"depth":[123],"estimation":[124],"semantic":[126],"segmentation.":[127],"Several":[128],"experiments":[129],"both":[130],"using":[131],"photo-realistic":[132],"real":[134],"data":[135],"gathered":[136],"from":[137],"multiple":[138],"viewpoints":[141],"effectiveness":[144],"approach":[148],"challenging":[150],"conditions":[152],"including":[153],"images":[154],"corrupted":[155],"heavy":[157],"camera":[160],"occlusions":[161]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":36},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":7}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
