{"id":"https://openalex.org/W3010599703","doi":"https://doi.org/10.1109/iros45743.2020.9340801","title":"Adversarial Generation of Informative Trajectories for Dynamics System Identification","display_name":"Adversarial Generation of Informative Trajectories for Dynamics System Identification","publication_year":2020,"publication_date":"2020-10-24","ids":{"openalex":"https://openalex.org/W3010599703","doi":"https://doi.org/10.1109/iros45743.2020.9340801","mag":"3010599703"},"language":"en","primary_location":{"id":"doi:10.1109/iros45743.2020.9340801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9340801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2003.01190","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083432303","display_name":"Marija Jegorova","orcid":"https://orcid.org/0000-0001-6319-9537"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Marija Jegorova","raw_affiliation_strings":["University of Edinburgh, UK","University of Edinburgh,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh,","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040435650","display_name":"Joshua Smith","orcid":"https://orcid.org/0000-0001-9249-5554"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Joshua Smith","raw_affiliation_strings":["University of Edinburgh, UK","University of Edinburgh,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh,","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082553836","display_name":"Michael Mistry","orcid":"https://orcid.org/0000-0003-3979-922X"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Michael Mistry","raw_affiliation_strings":["University of Edinburgh, UK","University of Edinburgh,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh,","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087823932","display_name":"Timothy M. Hospedales","orcid":"https://orcid.org/0000-0003-4867-7486"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Timothy Hospedales","raw_affiliation_strings":["University of Edinburgh, UK","University of Edinburgh,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh,","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":0.5196,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61414594,"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":"7109","last_page":"7115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7282678484916687},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.7017593383789062},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6869121789932251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5820524096488953},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.49345865845680237},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.47888725996017456},{"id":"https://openalex.org/keywords/inertial-frame-of-reference","display_name":"Inertial frame of reference","score":0.45595410466194153},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45459914207458496},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.43255022168159485},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42747679352760315},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.4157774746417999},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.199066162109375},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.07847860455513}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7282678484916687},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7017593383789062},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6869121789932251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5820524096488953},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.49345865845680237},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.47888725996017456},{"id":"https://openalex.org/C173386949","wikidata":"https://www.wikidata.org/wiki/Q192735","display_name":"Inertial frame of reference","level":2,"score":0.45595410466194153},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45459914207458496},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.43255022168159485},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42747679352760315},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.4157774746417999},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.199066162109375},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.07847860455513},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/iros45743.2020.9340801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9340801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2003.01190","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.01190","pdf_url":"https://arxiv.org/pdf/2003.01190","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/74322768-521e-41fa-be19-d1c1e7c8ae24","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.11820/74322768-521e-41fa-be19-d1c1e7c8ae24","pdf_url":"https://www.research.ed.ac.uk/files/158668216/Adversarial_Generation_JEGOROVA_DOA01072020_AFV.pdf","source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jegorova, M, Smith, J, Mistry, M & Hospedales, T M 2021, Adversarial Generation of Informative Trajectories for Dynamics System Identification. in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Institute of Electrical and Electronics Engineers, pp. 7109 - 7115, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, Nevada, United States, 25/10/20. https://doi.org/10.1109/IROS45743.2020.9340801","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.ed.ac.uk:publications/74322768-521e-41fa-be19-d1c1e7c8ae24","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/74322768-521e-41fa-be19-d1c1e7c8ae24","pdf_url":"http://hdl.handle.net/20.500.11820/74322768-521e-41fa-be19-d1c1e7c8ae24","source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jegorova, M, Smith, J, Mistry, M & Hospedales, T M 2021, Adversarial Generation of Informative Trajectories for Dynamics System Identification. in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Institute of Electrical and Electronics Engineers, pp. 7109 - 7115, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, Nevada, United States, 25/10/20. https://doi.org/10.1109/IROS45743.2020.9340801","raw_type":"contributionToPeriodical"},{"id":"mag:3010599703","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2003.01190.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2003.01190","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2003.01190","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2003.01190","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.01190","pdf_url":"https://arxiv.org/pdf/2003.01190","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2001524797","https://openalex.org/W2035587171","https://openalex.org/W2078856056","https://openalex.org/W2099471712","https://openalex.org/W2162737890","https://openalex.org/W2169017219","https://openalex.org/W2893749619","https://openalex.org/W2900424942","https://openalex.org/W2963277051","https://openalex.org/W2963470893","https://openalex.org/W2963684088","https://openalex.org/W2963841322","https://openalex.org/W2963966654","https://openalex.org/W2971482891","https://openalex.org/W2978280891","https://openalex.org/W2991756821","https://openalex.org/W3004587862","https://openalex.org/W3090761692","https://openalex.org/W3102937540","https://openalex.org/W4299796063","https://openalex.org/W6685352114","https://openalex.org/W6718092244","https://openalex.org/W6735965560","https://openalex.org/W6753914649","https://openalex.org/W6755312952","https://openalex.org/W6769550096","https://openalex.org/W6775258189","https://openalex.org/W6785448149"],"related_works":["https://openalex.org/W3131357870","https://openalex.org/W3117307549","https://openalex.org/W2566277644","https://openalex.org/W2801572960","https://openalex.org/W2765291105","https://openalex.org/W108922585","https://openalex.org/W3198294736","https://openalex.org/W2973457379","https://openalex.org/W3003152535","https://openalex.org/W3162689122","https://openalex.org/W2330701138","https://openalex.org/W3183848994","https://openalex.org/W2941124771","https://openalex.org/W3013434224","https://openalex.org/W2979215460","https://openalex.org/W3080412179","https://openalex.org/W2521871693","https://openalex.org/W3199291608","https://openalex.org/W2812202668","https://openalex.org/W3010923667"],"abstract_inverted_index":{"Dnamic":[0],"System":[1],"Identification":[2],"approaches":[3],"usually":[4],"heavily":[5],"rely":[6],"on":[7],"evolutionary":[8],"and":[9,37,67,95,116,140,157],"gradient-based":[10],"optimisation":[11,27],"techniques":[12,28,144],"to":[13,30,51,71,84,110,132,141],"produce":[14,111],"optimal":[15],"excitation":[16,118,148],"trajectories":[17,139,149],"for":[18,39,46,145],"determining":[19],"the":[20,73,92,98,101,121,128,178],"physical":[21],"parameters":[22],"of":[23,97,103,114,123],"robot":[24],"platforms.":[25],"Current":[26],"tend":[29],"generate":[31],"single":[32],"trajectories.":[33,119],"This":[34],"is":[35,127],"expensive,":[36],"intractable":[38],"longer":[40,78],"trajectories,":[41,60],"thus":[42],"limiting":[43],"their":[44],"efficacy":[45],"system":[47,134,175],"identification.":[48],"We":[49,161],"propose":[50],"tackle":[52],"this":[53,86,126],"issue":[54],"by":[55,90],"using":[56],"multiple":[57,137],"shorter":[58],"cyclic":[59,138],"which":[61],"can":[62],"be":[63],"generated":[64],"in":[65,153],"parallel,":[66],"subsequently":[68],"combined":[69],"together":[70],"achieve":[72],"same":[74],"effect":[75],"as":[76],"a":[77],"trajectory.":[79],"Crucially,":[80],"we":[81],"show":[82,162],"how":[83],"scale":[85],"approach":[87,165],"even":[88],"further":[89],"increasing":[91],"generation":[93],"speed":[94],"quality":[96],"dataset":[99],"through":[100],"use":[102],"generative":[104],"adversarial":[105],"network":[106],"(GAN)":[107],"based":[108],"architectures":[109],"large":[112],"databases":[113],"valid":[115],"diverse":[117,152],"To":[120],"best":[122],"our":[124,164],"knowledge,":[125],"first":[129],"robotics":[130],"work":[131],"explore":[133],"identification":[135,176],"with":[136],"develop":[142],"GAN-based":[143],"scaleably":[146],"producing":[147],"that":[150,163],"are":[151],"both":[154],"control":[155],"parameter":[156,159],"inertial":[158],"spaces.":[160],"dramatically":[166],"accelerates":[167],"trajectory":[168],"optimisation,":[169],"while":[170],"simultaneously":[171],"providing":[172],"more":[173],"accurate":[174],"than":[177],"conventional":[179],"approach.":[180]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}