{"id":"https://openalex.org/W4408126068","doi":"https://doi.org/10.1109/tim.2025.3545493","title":"Hierarchical Compensation of Robot Positioning Error: Addressing Geometric and Nongeometric Influences","display_name":"Hierarchical Compensation of Robot Positioning Error: Addressing Geometric and Nongeometric Influences","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408126068","doi":"https://doi.org/10.1109/tim.2025.3545493"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2025.3545493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3545493","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":"Shuo Xu","orcid":"https://orcid.org/0009-0004-3204-6027"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Xu","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0004-3204-6027","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036024060","display_name":"Xiaohui Jia","orcid":"https://orcid.org/0000-0003-2092-8626"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Jia","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-2092-8626","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057515159","display_name":"Jinyue Liu","orcid":"https://orcid.org/0000-0003-4189-9027"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyue Liu","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-4189-9027","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100703334","display_name":"Tiejun Li","orcid":"https://orcid.org/0000-0003-1361-1014"},"institutions":[{"id":"https://openalex.org/I34155123","display_name":"Hebei University of Science and Technology","ror":"https://ror.org/05h3pkk68","country_code":"CN","type":"education","lineage":["https://openalex.org/I34155123"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiejun Li","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang, China"],"raw_orcid":"https://orcid.org/0000-0003-1361-1014","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang, China","institution_ids":["https://openalex.org/I34155123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.4253,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.95492755,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9437000155448914,"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":0.9437000155448914,"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/T12006","display_name":"Ergonomics and Musculoskeletal Disorders","score":0.926800012588501,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6125611662864685},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.5501369833946228},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5082961916923523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5071840286254883},{"id":"https://openalex.org/keywords/geometric-modeling","display_name":"Geometric modeling","score":0.45408207178115845},{"id":"https://openalex.org/keywords/solid-modeling","display_name":"Solid modeling","score":0.4325125217437744},{"id":"https://openalex.org/keywords/geometric-shape","display_name":"Geometric shape","score":0.4290609359741211},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42477571964263916},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2411489486694336},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1768190860748291}],"concepts":[{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6125611662864685},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.5501369833946228},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5082961916923523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5071840286254883},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.45408207178115845},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.4325125217437744},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.4290609359741211},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42477571964263916},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2411489486694336},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1768190860748291},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2025.3545493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3545493","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/G1901044022","display_name":null,"funder_award_id":"U24A6005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4314168795","display_name":null,"funder_award_id":"U20A20283","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":49,"referenced_works":["https://openalex.org/W1987363494","https://openalex.org/W2011556650","https://openalex.org/W2026850673","https://openalex.org/W2080162662","https://openalex.org/W2413066658","https://openalex.org/W2414319016","https://openalex.org/W2460495915","https://openalex.org/W2747588053","https://openalex.org/W2756924539","https://openalex.org/W2884171416","https://openalex.org/W2909047179","https://openalex.org/W2946829601","https://openalex.org/W2997362232","https://openalex.org/W2997398064","https://openalex.org/W3010812702","https://openalex.org/W3032134541","https://openalex.org/W3033453331","https://openalex.org/W3108449827","https://openalex.org/W3137669920","https://openalex.org/W3198665734","https://openalex.org/W4206037272","https://openalex.org/W4229050707","https://openalex.org/W4239366869","https://openalex.org/W4281751072","https://openalex.org/W4296620536","https://openalex.org/W4304701300","https://openalex.org/W4306740371","https://openalex.org/W4306907926","https://openalex.org/W4318337988","https://openalex.org/W4319999793","https://openalex.org/W4320487090","https://openalex.org/W4320719842","https://openalex.org/W4321021754","https://openalex.org/W4362575530","https://openalex.org/W4365449511","https://openalex.org/W4365816857","https://openalex.org/W4376457100","https://openalex.org/W4378569187","https://openalex.org/W4386379625","https://openalex.org/W4386391043","https://openalex.org/W4387100648","https://openalex.org/W4387578484","https://openalex.org/W4387647149","https://openalex.org/W4390081905","https://openalex.org/W4399701667","https://openalex.org/W4400187749","https://openalex.org/W4401014272","https://openalex.org/W4402053102","https://openalex.org/W4402388037"],"related_works":["https://openalex.org/W2124313076","https://openalex.org/W4235802564","https://openalex.org/W3139854383","https://openalex.org/W3010256417","https://openalex.org/W2332420753","https://openalex.org/W1906812549","https://openalex.org/W2086709482","https://openalex.org/W1629863428","https://openalex.org/W4283712015","https://openalex.org/W2164953988"],"abstract_inverted_index":{"Aiming":[0,61],"at":[1,62],"the":[2,5,10,63,70,80,84,89,94,98,104,125,129,132,154,165,185,203],"problem":[3],"that":[4,153],"absolute":[6,158],"positioning":[7,43,91,138],"accuracy":[8],"of":[9,41,83,93,128,134,137,164,189,195],"robot":[11,42,85,95],"end-effector":[12,96],"decreases":[13],"due":[14],"to":[15,121],"geometric":[16,81,177],"errors,":[17,27],"such":[18,28],"as":[19,29,97,120],"those":[20],"from":[21],"manufacturing":[22],"and":[23,25,32,54,67,112,123,160,173,179,187],"assembly,":[24],"nongeometric":[26,126,180],"joint":[30],"flexibility":[31],"gear":[33],"clearance":[34],"in":[35],"industry,":[36],"a":[37,55,76,143,199],"hierarchical":[38,135],"compensation":[39,136],"method":[40],"error":[44,82,92,139,162,167,178,181],"is":[45,86,110,115,140],"proposed.":[46,60],"First,":[47],"an":[48],"improved":[49],"crayfish":[50],"optimization":[51],"algorithm":[52],"(ICOA)":[53],"multiobjective":[56,77],"ICOA":[57,118],"(MOICOA)":[58],"are":[59,73,168],"model":[64,109],"condition":[65],"number":[66],"position":[68,166],"distribution,":[69],"identification":[71],"points":[72],"optimized":[74,116],"by":[75,117,170],"approach.":[78],"Moreover,":[79],"compensated":[87],"with":[88],"minimum":[90],"goal.":[99],"Second,":[100],"based":[101],"on":[102],"data-driven,":[103],"Gaussian":[105],"process":[106],"regression":[107],"(GPR)":[108],"established,":[111],"its":[113],"hyperparameter":[114],"so":[119],"regress":[122],"compensate":[124],"errors":[127],"robot.":[130,148],"Finally,":[131],"experiment":[133],"conducted":[141],"using":[142],"universal":[144],"six-degree-of-freedom":[145],"(6-DOF)":[146],"serial":[147],"The":[149,192],"experimental":[150],"results":[151,194],"show":[152],"maximum":[155],"error,":[156,159],"mean":[157],"root-mean-square":[161],"(RMSE)":[163],"reduced":[169],"95.43%,":[171],"92.39%,":[172],"95.01%,":[174],"respectively,":[175],"after":[176],"compensation,":[182],"which":[183],"verifies":[184],"correctness":[186],"effectiveness":[188],"this":[190,196],"method.":[191],"research":[193],"article":[197],"provide":[198],"theoretical":[200],"basis":[201],"for":[202],"robot\u2019s":[204],"high-precision":[205],"operation.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
