{"id":"https://openalex.org/W3186869035","doi":"https://doi.org/10.23919/acc50511.2021.9482981","title":"Contact Pose Identification for Peg-in-Hole Assembly under Uncertainties","display_name":"Contact Pose Identification for Peg-in-Hole Assembly under Uncertainties","publication_year":2021,"publication_date":"2021-05-25","ids":{"openalex":"https://openalex.org/W3186869035","doi":"https://doi.org/10.23919/acc50511.2021.9482981","mag":"3186869035"},"language":"en","primary_location":{"id":"doi:10.23919/acc50511.2021.9482981","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc50511.2021.9482981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 American Control Conference (ACC)","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/A5050808028","display_name":"Shiyu Jin","orcid":"https://orcid.org/0000-0002-6475-5942"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiyu Jin","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101715656","display_name":"Xinghao Zhu","orcid":"https://orcid.org/0009-0002-8078-1531"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinghao Zhu","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100709173","display_name":"Changhao Wang","orcid":"https://orcid.org/0000-0002-5753-1991"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Changhao Wang","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064077634","display_name":"Masayoshi Tomizuka","orcid":"https://orcid.org/0000-0003-0206-6639"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Masayoshi Tomizuka","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5274,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.82403723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"48","last_page":"53"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T11799","display_name":"Adhesion, Friction, and Surface Interactions","score":0.9941999912261963,"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"}},{"id":"https://openalex.org/T11301","display_name":"Advanced Surface Polishing Techniques","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/peg-ratio","display_name":"PEG ratio","score":0.6075565218925476},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5800194144248962},{"id":"https://openalex.org/keywords/admittance","display_name":"Admittance","score":0.5583401918411255},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5432854890823364},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5323802828788757},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.4929482936859131},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4921724200248718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47320884466171265},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4675632417201996},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.45167794823646545},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3687468469142914},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33388110995292664},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16927698254585266},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.15802529454231262},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12513267993927002},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.057833850383758545}],"concepts":[{"id":"https://openalex.org/C54400483","wikidata":"https://www.wikidata.org/wiki/Q1793202","display_name":"PEG ratio","level":2,"score":0.6075565218925476},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5800194144248962},{"id":"https://openalex.org/C108811297","wikidata":"https://www.wikidata.org/wiki/Q214518","display_name":"Admittance","level":3,"score":0.5583401918411255},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5432854890823364},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5323802828788757},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.4929482936859131},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4921724200248718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47320884466171265},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4675632417201996},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.45167794823646545},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3687468469142914},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33388110995292664},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16927698254585266},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.15802529454231262},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12513267993927002},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.057833850383758545},{"id":"https://openalex.org/C17829176","wikidata":"https://www.wikidata.org/wiki/Q179043","display_name":"Electrical impedance","level":2,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc50511.2021.9482981","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc50511.2021.9482981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 American Control Conference (ACC)","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":24,"referenced_works":["https://openalex.org/W1560270123","https://openalex.org/W1560840829","https://openalex.org/W1938885652","https://openalex.org/W2008731016","https://openalex.org/W2077457254","https://openalex.org/W2124109017","https://openalex.org/W2129190609","https://openalex.org/W2155007355","https://openalex.org/W2162207896","https://openalex.org/W2163605009","https://openalex.org/W2526166478","https://openalex.org/W2553722312","https://openalex.org/W2605102758","https://openalex.org/W2768879211","https://openalex.org/W2917550650","https://openalex.org/W2963188159","https://openalex.org/W2964161785","https://openalex.org/W2967129319","https://openalex.org/W2967717386","https://openalex.org/W2968095426","https://openalex.org/W3003618985","https://openalex.org/W4234486210","https://openalex.org/W6682849425","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2963891724","https://openalex.org/W2112002268","https://openalex.org/W2295869952","https://openalex.org/W1726816713","https://openalex.org/W2566455068","https://openalex.org/W3093612317","https://openalex.org/W2105267066","https://openalex.org/W2613736958","https://openalex.org/W2162639903","https://openalex.org/W1865242774"],"abstract_inverted_index":{"Peg-in-hole":[0],"assembly":[1,126],"is":[2,9,58,80],"a":[3,31,41,55,66],"challenging":[4],"contact-rich":[5],"manipulation":[6],"task.":[7],"There":[8],"no":[10],"general":[11],"solution":[12],"to":[13,34,70,82,88,114,123,135],"identify":[14],"the":[15,21,24,36,47,50,61,72,84,89,92,98,101,106,117,124,133,137],"relative":[16],"position":[17],"and":[18,23,60,104,110],"orientation":[19],"between":[20],"peg":[22,48,99],"hole.":[25],"In":[26,91],"this":[27],"paper,":[28],"we":[29],"propose":[30],"novel":[32],"method":[33,119],"classify":[35,83],"contact":[37,44,73,85],"poses":[38,86],"based":[39],"on":[40],"sequence":[42],"of":[43,68,127],"measurements.":[45],"When":[46],"contacts":[49,62],"hole":[51],"with":[52],"pose":[53],"uncertainties,":[54],"tilt-then-rotate":[56],"strategy":[57],"applied,":[59],"are":[63,112],"measured":[64],"as":[65],"group":[67],"patterns":[69],"encode":[71],"pose.":[74],"A":[75],"convolutional":[76],"neural":[77],"network":[78],"(CNN)":[79],"trained":[81],"according":[87],"patterns.":[90],"end,":[93],"an":[94],"admittance":[95],"controller":[96],"guides":[97],"towards":[100],"error":[102],"direction":[103],"finishes":[105],"peg-in-hole":[107,125],"assembly.":[108],"Simulations":[109],"experiments":[111],"provided":[113],"show":[115],"that":[116],"proposed":[118],"can":[120],"be":[121],"applied":[122],"different":[128],"geometries.":[129],"We":[130],"also":[131],"demonstrate":[132],"ability":[134],"alleviate":[136],"sim-to-real":[138],"gap.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
