{"id":"https://openalex.org/W2000676112","doi":"https://doi.org/10.1109/icra.2014.6907358","title":"Online parameter optimization in robotic force controlled assembly processes","display_name":"Online parameter optimization in robotic force controlled assembly processes","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2000676112","doi":"https://doi.org/10.1109/icra.2014.6907358","mag":"2000676112"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2014.6907358","doi":"https://doi.org/10.1109/icra.2014.6907358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2014.6907358","pdf_url":null,"source":{"id":"https://openalex.org/S4210217939","display_name":"Proceedings - IEEE International Conference on Robotics and Automation/Proceedings","issn_l":"1050-4729","issn":["1050-4729","2577-087X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5101454916","display_name":"Hongtai Cheng","orcid":"https://orcid.org/0000-0001-7579-5803","observed_orcids":["https://orcid.org/0000-0001-7579-5803"]},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongtai Cheng","raw_affiliation_strings":["Department of Mechanical Engineering and Automation, Texas State University, USA","Department of Mechanical Engineering and Automation, North East University, China and the Ingram School of Engineering, Texas State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering and Automation, Texas State University, USA","institution_ids":["https://openalex.org/I13511017"]},{"raw_affiliation_string":"Department of Mechanical Engineering and Automation, North East University, China and the Ingram School of Engineering, Texas State University, USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101688278","display_name":"Heping Chen","orcid":"https://orcid.org/0000-0002-1045-8977","observed_orcids":["https://orcid.org/0000-0002-1045-8977"]},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heping Chen","raw_affiliation_strings":["Ingram School of Engineering, Texas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ingram School of Engineering, Texas State University","institution_ids":["https://openalex.org/I13511017"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I13511017"],"apc_list":null,"apc_paid":null,"fwci":2.8338,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.89754553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"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/T10653","display_name":"Robot Manipulation and Learning","score":0.7660999894142151,"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"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.7660999894142151,"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/T11159","display_name":"Manufacturing Process and Optimization","score":0.0828000009059906,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10571","display_name":"Robotic Mechanisms and Dynamics","score":0.022199999541044235,"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/online-parameter-tuning","display_name":"online parameter tuning","score":0.9539999961853027},{"id":"https://openalex.org/keywords/robotic-assembly","display_name":"robotic assembly","score":0.9520000219345093},{"id":"https://openalex.org/keywords/gaussian-process-regression","display_name":"Gaussian process regression","score":0.9290000200271606},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.9559999704360962},{"id":"https://openalex.org/keywords/exploration-exploitation-trade-off","display_name":"exploration-exploitation balance","score":0.7570000290870667},{"id":"https://openalex.org/keywords/switching-criterion","display_name":"switching criterion","score":0.7990000247955322},{"id":"https://openalex.org/keywords/peg-in-hole-assembly","display_name":"peg-in-hole assembly","score":0.7889999747276306},{"id":"https://openalex.org/keywords/surrogate-modeling","display_name":"surrogate models","score":0.6010000109672546},{"id":"https://openalex.org/keywords/model-based-optimization","display_name":"model-based optimization","score":0.5070000290870667}],"concepts":[{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.7597721815109253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7031692266464233},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.6982792019844055},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6832201480865479},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6518908739089966},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5113808512687683},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43193936347961426},{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.4190411865711212},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3263343274593353},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.31060922145843506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2864091396331787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2574891149997711},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14409330487251282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13813117146492004},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2014.6907358","doi":"https://doi.org/10.1109/icra.2014.6907358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2014.6907358","pdf_url":null,"source":{"id":"https://openalex.org/S4210217939","display_name":"Proceedings - IEEE International Conference on Robotics and Automation/Proceedings","issn_l":"1050-4729","issn":["1050-4729","2577-087X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5378999710083008}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W38425204","https://openalex.org/W1568345957","https://openalex.org/W1746819321","https://openalex.org/W1921773653","https://openalex.org/W1983354559","https://openalex.org/W2010048770","https://openalex.org/W2011174137","https://openalex.org/W2016080724","https://openalex.org/W2037968013","https://openalex.org/W2055648192","https://openalex.org/W2056390950","https://openalex.org/W2135398081","https://openalex.org/W2137786594","https://openalex.org/W2143075311","https://openalex.org/W2402776809","https://openalex.org/W2468462628","https://openalex.org/W2626867313","https://openalex.org/W4211049957","https://openalex.org/W4300570015"],"related_works":["https://openalex.org/W2291456410","https://openalex.org/W3211534007","https://openalex.org/W1495805583","https://openalex.org/W2060514515","https://openalex.org/W2983340729","https://openalex.org/W2581571117","https://openalex.org/W2002872958","https://openalex.org/W1967428708","https://openalex.org/W4232511668","https://openalex.org/W2122036969"],"abstract_inverted_index":{"In":[0,44],"the":[1,7,22,28,35,61,64,80,85,100,108,116,128,136,150,153,172],"high":[2],"precision":[3],"robotic":[4],"assembly":[5,177],"processes,":[6],"process":[8,65,81,130,133,178],"parameters":[9,66],"have":[10],"to":[11,16,18,59,78,89,99,106,126,134,163],"be":[12],"tuned":[13],"in":[14],"order":[15],"adapt":[17],"variations":[19],"and":[20,31,67,110,131,156,160,181],"satisfy":[21],"performance":[23],"requirements.":[24],"However,":[25],"because":[26],"of":[27,34,87,119,152,175],"modeling":[29],"difficulty":[30],"low":[32],"efficiency":[33,159],"existing":[36],"solutions,":[37],"this":[38,45],"task":[39],"is":[40,52,57,76,97,124,171],"usually":[41],"performed":[42,141],"offline.":[43],"paper,":[46],"an":[47],"online":[48],"parameter":[49,179],"optimization":[50,129,180],"method":[51,170],"developed.":[53],"Gaussian":[54],"Process":[55],"Regression(GPR)":[56],"utilized":[58],"model":[60],"relationship":[62],"between":[63],"system":[68],"performance.":[69],"The":[70,146,168],"GPR":[71],"surrogated":[72],"Bayesian":[73],"Optimization":[74],"Algorithm(GPRBOA)":[75],"proposed":[77,125,154,169],"optimize":[79],"parameters.":[82],"To":[83,113],"reduce":[84,135],"risk":[86],"converging":[88],"a":[90,93,121,143],"local":[91],"minimum,":[92],"random":[94],"variation":[95],"factor":[96],"added":[98],"Lower":[101],"Confidence":[102],"Bound(LCB)":[103],"acquisition":[104],"function":[105],"balance":[107],"exploration":[109],"exploitation":[111],"processes.":[112],"deal":[114],"with":[115],"computational":[117,137],"burden":[118],"GPR,":[120],"switching":[122],"criterion":[123],"coordinate":[127],"production":[132],"complexity.":[138],"Experiments":[139],"were":[140],"using":[142],"peg-in-hole":[144],"process.":[145],"experimental":[147],"results":[148],"verify":[149],"effectiveness":[151],"algorithm":[155],"demonstrate":[157],"its":[158],"accuracy":[161],"compared":[162],"Design":[164],"Of":[165],"Experiment(DOE)":[166],"methods.":[167],"first":[173],"attempt":[174],"model-driven":[176],"will":[182],"generate":[183],"big":[184],"economic":[185],"impact.":[186]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":6},{"year":2015,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}
