{"id":"https://openalex.org/W4406208549","doi":"https://doi.org/10.1109/tim.2025.3527596","title":"Uncertainty Estimation Based on Error Propagation Law for Multi-Robot Pose Graph Merging","display_name":"Uncertainty Estimation Based on Error Propagation Law for Multi-Robot Pose Graph Merging","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406208549","doi":"https://doi.org/10.1109/tim.2025.3527596"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2025.3527596","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3527596","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Transactions on Instrumentation and Measurement","raw_type":"journal-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":null,"display_name":"Yuxuan Feng","orcid":"https://orcid.org/0009-0003-7935-453X"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Feng","raw_affiliation_strings":["School of Electronic and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0003-7935-453X","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hao Fang","orcid":"https://orcid.org/0000-0002-9627-0325"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Fang","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9627-0325","affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7588,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.84980077,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"11"},"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":0.9617000222206116,"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":0.9617000222206116,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9544000029563904,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9466999769210815,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/jacobian-matrix-and-determinant","display_name":"Jacobian matrix and determinant","score":0.7728532552719116},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6610678434371948},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5821999311447144},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5639978647232056},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5563406944274902},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5272014737129211},{"id":"https://openalex.org/keywords/propagation-of-uncertainty","display_name":"Propagation of uncertainty","score":0.49443793296813965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4585639238357544},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4419916868209839},{"id":"https://openalex.org/keywords/robot-kinematics","display_name":"Robot kinematics","score":0.4213806986808777},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.36847516894340515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3593593239784241},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3200942575931549},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.277612566947937},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21103230118751526}],"concepts":[{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.7728532552719116},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6610678434371948},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5821999311447144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5639978647232056},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5563406944274902},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5272014737129211},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.49443793296813965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4585639238357544},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4419916868209839},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.4213806986808777},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.36847516894340515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3593593239784241},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3200942575931549},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.277612566947937},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21103230118751526},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2025.3527596","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3527596","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8508485082","display_name":null,"funder_award_id":"62133002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1574773379","https://openalex.org/W1603426217","https://openalex.org/W1756216659","https://openalex.org/W2011897632","https://openalex.org/W2046918204","https://openalex.org/W2109271936","https://openalex.org/W2153054365","https://openalex.org/W2155653863","https://openalex.org/W2461937780","https://openalex.org/W2547811925","https://openalex.org/W2564085365","https://openalex.org/W2774154105","https://openalex.org/W2803446646","https://openalex.org/W2809051097","https://openalex.org/W2884229198","https://openalex.org/W2891820683","https://openalex.org/W2960971247","https://openalex.org/W2963479576","https://openalex.org/W2964025948","https://openalex.org/W2971269667","https://openalex.org/W3003257820","https://openalex.org/W3012268014","https://openalex.org/W3095174237","https://openalex.org/W3139270484","https://openalex.org/W3160440378","https://openalex.org/W3192951112","https://openalex.org/W3214551689","https://openalex.org/W4313306306","https://openalex.org/W4324119544","https://openalex.org/W4362500683","https://openalex.org/W4386076459","https://openalex.org/W4387682177","https://openalex.org/W4392224253","https://openalex.org/W4394585839","https://openalex.org/W4396909836","https://openalex.org/W4403779097","https://openalex.org/W6800216578","https://openalex.org/W6873391835"],"related_works":["https://openalex.org/W2007405763","https://openalex.org/W3136087161","https://openalex.org/W1486373823","https://openalex.org/W2119578520","https://openalex.org/W2053762185","https://openalex.org/W2913611334","https://openalex.org/W2135044092","https://openalex.org/W2099329708","https://openalex.org/W1554233026","https://openalex.org/W2402852349"],"abstract_inverted_index":{"In":[0,66],"the":[1,15,22,45,74,100,104,109,119,174,179,195],"domain":[2],"of":[3,17,24,47,54,76,103,153],"collaborative":[4],"Simultaneous":[5],"Localization":[6],"and":[7,44,62,79,125,165,178,194],"Mapping":[8],"(CSLAM),":[9],"a":[10,81,92,132,137,147,151,158,183,201],"significant":[11],"challenge":[12],"is":[13,28,187],"enhancing":[14],"accuracy":[16],"multi-robot":[18,71],"trajectory":[19,72,166],"merging.":[20],"To":[21],"best":[23],"our":[25,155,170],"knowledge,":[26],"there":[27],"currently":[29],"no":[30],"relevant":[31],"literature":[32],"addressing":[33],"uncertainty":[34,83],"estimation":[35,84,204],"for":[36],"relative":[37],"coordinate":[38],"transformations":[39],"under":[40],"indirect":[41],"data":[42],"association":[43],"difficulty":[46],"this":[48,67],"issue":[49],"stems":[50],"from":[51,121],"covariance":[52],"propagation":[53,111],"three":[55],"primary":[56],"information":[57],"sources":[58],"(both":[59],"single-robot":[60,123],"pose":[61,77,87,124,139],"inter-robot":[63,126],"loop":[64,127],"closure).":[65],"paper,":[68],"we":[69,90,130],"represent":[70],"in":[73,161,203],"form":[75],"graph":[78],"present":[80],"novel":[82],"with":[85],"compound":[86,138],"(UECP).":[88],"Initially,":[89],"develop":[91],"cost":[93],"function":[94],"through":[95],"Lie":[96],"algebra,":[97],"followed":[98],"by":[99,135],"direct":[101],"differentiation":[102,193],"Jacobian.":[105],"We":[106],"then":[107],"apply":[108],"error":[110,205],"law":[112],"(EPL)":[113],"to":[114,207],"estimate":[115],"uncertainty,":[116],"which":[117,141,172],"incorporates":[118],"covariances":[120],"both":[122,162,191],"closure.":[128],"Ultimately,":[129],"propose":[131],"simplified":[133],"solution":[134],"implementing":[136],"technique,":[140],"merges":[142],"two":[143],"successive":[144],"poses":[145],"into":[146],"unified":[148],"estimate.":[149],"Through":[150],"series":[152],"experiments,":[154],"findings":[156],"indicate":[157],"substantial":[159],"enhancement":[160],"computation":[163,184],"time":[164,185],"alignment":[167],"accuracy.":[168],"Specifically,":[169],"approach,":[171],"leverages":[173],"derived":[175],"Jacobian":[176],"matrix":[177],"UECP":[180],"method,":[181],"achieves":[182],"that":[186],"more":[188],"efficient":[189],"than":[190],"automatic":[192],"EPL":[196],"method.":[197],"Additionally,":[198],"it":[199],"demonstrates":[200],"reduction":[202],"compared":[206],"state-of-the-art":[208],"methods.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
