{"id":"https://openalex.org/W2910440254","doi":"https://doi.org/10.1109/iros.2018.8593520","title":"Sensor Selection and Stage & Result Classifications for Automated Miniature Screwdriving","display_name":"Sensor Selection and Stage & Result Classifications for Automated Miniature Screwdriving","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2910440254","doi":"https://doi.org/10.1109/iros.2018.8593520","mag":"2910440254"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2018.8593520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2018.8593520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5100943262","display_name":"Xianyi Cheng","orcid":"https://orcid.org/0000-0001-8342-9459"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xianyi Cheng","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075727192","display_name":"Zhenzhong Jia","orcid":"https://orcid.org/0000-0001-5924-5502"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenzhong Jia","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000243758","display_name":"Ankit Bhatia","orcid":"https://orcid.org/0000-0002-0713-4103"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ankit Bhatia","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017028387","display_name":"Reuben M. Aronson","orcid":"https://orcid.org/0000-0002-8615-3715"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reuben M. Aronson","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002872886","display_name":"Matthew T. Mason","orcid":"https://orcid.org/0000-0002-2672-5689"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew T. Mason","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100943262"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.8462,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.81340902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"6078","last_page":"6085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9294999837875366,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9294999837875366,"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/T11201","display_name":"Metallurgy and Material Forming","score":0.9175999760627747,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/computer-science","display_name":"Computer science","score":0.6873447895050049},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6005555987358093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5845968127250671},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5284224152565002},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.512757420539856},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.47489967942237854},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42957496643066406},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4268849790096283},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4240623414516449},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41398143768310547},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4138854146003723}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6873447895050049},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6005555987358093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5845968127250671},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5284224152565002},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.512757420539856},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.47489967942237854},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42957496643066406},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4268849790096283},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4240623414516449},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41398143768310547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4138854146003723},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2018.8593520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2018.8593520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W79321582","https://openalex.org/W140867740","https://openalex.org/W599151612","https://openalex.org/W649525385","https://openalex.org/W1570713908","https://openalex.org/W2005430849","https://openalex.org/W2042072670","https://openalex.org/W2045272325","https://openalex.org/W2076706826","https://openalex.org/W2089966914","https://openalex.org/W2148239836","https://openalex.org/W2330820318","https://openalex.org/W2398139870","https://openalex.org/W2487770199","https://openalex.org/W2599330710","https://openalex.org/W2808777429","https://openalex.org/W6605731719","https://openalex.org/W6712900917","https://openalex.org/W6734955769","https://openalex.org/W6752124711"],"related_works":["https://openalex.org/W4402452563","https://openalex.org/W2250488071","https://openalex.org/W2356150353","https://openalex.org/W2018643641","https://openalex.org/W2380744779","https://openalex.org/W2967867994","https://openalex.org/W2469878540","https://openalex.org/W1999647744","https://openalex.org/W2765337000","https://openalex.org/W2951122819"],"abstract_inverted_index":{"Hundreds":[0],"of":[1,3,22,32,77,87,159],"billions":[2],"small":[4,45],"screws":[5],"are":[6,37,107],"assembled":[7],"in":[8,156],"consumer":[9],"electronics":[10],"industry":[11],"every":[12],"year,":[13],"yet":[14],"reliably":[15],"automating":[16],"the":[17,23,61,66,125,146,165],"screwdriving":[18,50,78,83],"process":[19],"remains":[20],"one":[21],"most":[24],"challenging":[25],"tasks.":[26],"Two":[27],"barriers":[28],"to":[29,64,123,133],"further":[30],"adoption":[31],"robotic":[33],"threaded":[34],"fastening":[35],"systems":[36],"system":[38,51],"cost":[39],"and":[40,57,80,98,103,129],"technical":[41],"challenges,":[42],"especially":[43],"for":[44,117],"screws.":[46],"An":[47],"affordable":[48],"intelligent":[49],"that":[52],"can":[53],"support":[54],"online":[55],"stage":[56,137,151],"result":[58,105],"classification":[59,96],"is":[60,121,143],"first":[62],"step":[63],"bridge":[65],"gap.":[67],"To":[68],"this":[69],"end,":[70],"starting":[71],"from":[72],"a":[73,81,114],"state":[74,166],"transition":[75,167],"graph":[76],"processes":[79],"labeled":[82],"dataset":[84],"(1862":[85],"runs":[86],"M1.4":[88],"screws)":[89],"on":[90,140],"multiple":[91],"sensor":[92,100,131,148],"signals,":[93],"we":[94],"develop":[95],"algorithms":[97],"perform":[99],"reduction.":[101],"Fast":[102],"accurate":[104],"classifiers":[106],"developed":[108,144],"using":[109,145],"linear":[110],"discriminant":[111],"analysis,":[112],"while":[113],"wrapper":[115],"method":[116],"feature":[118,127],"subset":[119,128],"selection":[120],"used":[122],"identify":[124],"optimal":[126,147],"corresponding":[130],"signals":[132],"reduce":[134],"cost.":[135],"A":[136],"classifier":[138,152],"based":[139],"decision":[141],"tree":[142],"subset.":[149],"The":[150],"achieves":[153],"high":[154],"accuracy":[155],"realtime":[157],"prediction":[158],"various":[160],"stages":[161],"when":[162],"augmented":[163],"with":[164],"graph.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}