{"id":"https://openalex.org/W2897689293","doi":"https://doi.org/10.1109/ijcnn.2018.8489055","title":"Learning Stable Movement Primitives by Finding a Suitable Fuzzy Lyapunov Function from Kinesthetic Demonstrations","display_name":"Learning Stable Movement Primitives by Finding a Suitable Fuzzy Lyapunov Function from Kinesthetic Demonstrations","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897689293","doi":"https://doi.org/10.1109/ijcnn.2018.8489055","mag":"2897689293"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103729695","display_name":"Samrat Dutta","orcid":null},"institutions":[{"id":"https://openalex.org/I16835326","display_name":"University of St Andrews","ror":"https://ror.org/02wn5qz54","country_code":"GB","type":"education","lineage":["https://openalex.org/I16835326"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Samrat Dutta","raw_affiliation_strings":["School of Computer Science, University of St Andrews North Haugh St Andrews KY16 9SX Fife, Scotland, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of St Andrews North Haugh St Andrews KY16 9SX Fife, Scotland, United Kingdom","institution_ids":["https://openalex.org/I16835326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053838336","display_name":"Swagat Kumar","orcid":"https://orcid.org/0000-0001-7405-3445"},"institutions":[{"id":"https://openalex.org/I16835326","display_name":"University of St Andrews","ror":"https://ror.org/02wn5qz54","country_code":"GB","type":"education","lineage":["https://openalex.org/I16835326"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Swagat Kumar","raw_affiliation_strings":["School of Computer Science, University of St Andrews North Haugh St Andrews KY16 9SX Fife, Scotland, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of St Andrews North Haugh St Andrews KY16 9SX Fife, Scotland, United Kingdom","institution_ids":["https://openalex.org/I16835326"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065056581","display_name":"Laxmidhar Behera","orcid":"https://orcid.org/0000-0003-1879-5609"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laxmidhar Behera","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9941999912261963,"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":0.9941999912261963,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9940000176429749,"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/T11236","display_name":"Control Systems and Identification","score":0.991100013256073,"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/computer-science","display_name":"Computer science","score":0.6138633489608765},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.544446587562561},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5334957242012024},{"id":"https://openalex.org/keywords/lyapunov-function","display_name":"Lyapunov function","score":0.5319986939430237},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5312079191207886},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.5059730410575867},{"id":"https://openalex.org/keywords/control-lyapunov-function","display_name":"Control-Lyapunov function","score":0.4440375864505768},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.443178653717041},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4404883086681366},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4335450828075409},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20934447646141052},{"id":"https://openalex.org/keywords/lyapunov-redesign","display_name":"Lyapunov redesign","score":0.19849243760108948},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.17496588826179504},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.11585009098052979},{"id":"https://openalex.org/keywords/lyapunov-exponent","display_name":"Lyapunov exponent","score":0.106792151927948}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6138633489608765},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.544446587562561},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5334957242012024},{"id":"https://openalex.org/C60640748","wikidata":"https://www.wikidata.org/wiki/Q2337858","display_name":"Lyapunov function","level":3,"score":0.5319986939430237},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5312079191207886},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.5059730410575867},{"id":"https://openalex.org/C201030206","wikidata":"https://www.wikidata.org/wiki/Q5165805","display_name":"Control-Lyapunov function","level":5,"score":0.4440375864505768},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.443178653717041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4404883086681366},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4335450828075409},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20934447646141052},{"id":"https://openalex.org/C37935115","wikidata":"https://www.wikidata.org/wiki/Q6707085","display_name":"Lyapunov redesign","level":4,"score":0.19849243760108948},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.17496588826179504},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.11585009098052979},{"id":"https://openalex.org/C191544260","wikidata":"https://www.wikidata.org/wiki/Q1238630","display_name":"Lyapunov exponent","level":3,"score":0.106792151927948},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/47dc55c9-fe1b-4717-bd0a-ebc1273d9789","is_oa":false,"landing_page_url":"https://research.edgehill.ac.uk/en/publications/47dc55c9-fe1b-4717-bd0a-ebc1273d9789","pdf_url":null,"source":{"id":"https://openalex.org/S4306402462","display_name":"Edge Hill University Research Information Repository (Edge Hill University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165525304","host_organization_name":"Edge Hill University","host_organization_lineage":["https://openalex.org/I165525304"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Dutta, S, Kumar, S & Behera, L 2018, Learning Stable Movement Primitives by Finding a Suitable Fuzzy Lyapunov Function from Kinesthetic Demonstrations. in Proceedings of the International Joint Conference on Neural Networks. Proceedings of the International Joint Conference on Neural Networks, vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., 2018 International Joint Conference on Neural Networks, Rio de Janeiro, Brazil, 8/07/18. https://doi.org/10.1109/IJCNN.2018.8489055","raw_type":"bookPart"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1601795611","https://openalex.org/W1746819321","https://openalex.org/W1963873191","https://openalex.org/W1976606095","https://openalex.org/W1996378889","https://openalex.org/W2003155905","https://openalex.org/W2063471043","https://openalex.org/W2091714857","https://openalex.org/W2113698995","https://openalex.org/W2129202194","https://openalex.org/W2136719407","https://openalex.org/W2146055337","https://openalex.org/W2148112459","https://openalex.org/W2397394694","https://openalex.org/W2412669390","https://openalex.org/W2474718355","https://openalex.org/W2552320543","https://openalex.org/W2735700496","https://openalex.org/W2900376083","https://openalex.org/W2963047720","https://openalex.org/W4211049957","https://openalex.org/W4213345774","https://openalex.org/W6629804754"],"related_works":["https://openalex.org/W3217133416","https://openalex.org/W2349796700","https://openalex.org/W1970635650","https://openalex.org/W2126112326","https://openalex.org/W2475132469","https://openalex.org/W1976574339","https://openalex.org/W2766646824","https://openalex.org/W1996957550","https://openalex.org/W1979297933","https://openalex.org/W2588600327"],"abstract_inverted_index":{"Transferring":[0],"skills":[1],"to":[2,53,84,126,148],"roUots":[3],"through":[4],"human":[5,20],"demonstrations":[6,13,59,93],"is":[7,111,133,172],"an":[8,118],"interesting":[9],"problem.":[10],"Locally":[11],"generated":[12],"of":[14,30,50,91],"reaching":[15],"motion,":[16],"given":[17],"by":[18],"a":[19,26,47,61,71,97,128,136,145,150,167,176,184],"teacher":[21],"are":[22,94],"generally":[23],"encoded":[24,95],"in":[25,96,117,123,135,166],"dynamical":[27,51],"model.":[28,155,169],"Stability":[29],"this":[31],"encoding":[32],"system":[33,52],"demands":[34],"great":[35],"attention":[36],"while":[37],"learning":[38],"the":[39,78,89,92,109,114,141],"model":[40,143],"parameters.":[41],"In":[42],"that":[43,68,76,86,138],"context,":[44],"we":[45],"present":[46],"new":[48,134],"architecture":[49,132],"learn":[54,127,161],"movement":[55],"primitives":[56],"from":[57],"multiple":[58],"exploiting":[60],"fuzzy":[62,129,146],"Lyapunov":[63,73],"function":[64,74],"(FLF).":[65],"We":[66],"assume":[67],"there":[69],"exists":[70],"natural":[72],"(LF)":[75],"associates":[77],"demonstrations.":[79],"The":[80,121,156,170],"proposed":[81,157],"FLF":[82,110,122],"tries":[83],"approximate":[85],"LF.":[87],"First,":[88],"dynamics":[90,116],"regressive":[98],"model,":[99],"learnt":[100,115],"using":[101],"Gaussian":[102],"mixture":[103],"regression":[104],"with":[105,144,183],"EM":[106],"algorithm.":[107],"Then":[108],"searched":[112],"involving":[113],"optimization":[119],"process.":[120],"turn":[124],"helps":[125],"controller.":[130],"Our":[131],"sense":[137],"it":[139],"combines":[140],"probabilistic":[142],"controller":[147],"create":[149],"globally":[151],"asymptotically":[152],"stable":[153],"motion":[154],"algorithm":[158,171],"can":[159],"simultaneously":[160],"position":[162],"and":[163,180],"orientation":[164],"profiles":[165],"single":[168],"experimentally":[173],"validated":[174],"on":[175],"commercially":[177],"available":[178],"manipulator":[179],"also":[181],"compared":[182],"state-of-the-art":[185],"technique.":[186]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
