{"id":"https://openalex.org/W4394564202","doi":"https://doi.org/10.1109/lra.2024.3386053","title":"Tube-NeRF: Efficient Imitation Learning of Visuomotor Policies From MPC via Tube-Guided Data Augmentation and NeRFs","display_name":"Tube-NeRF: Efficient Imitation Learning of Visuomotor Policies From MPC via Tube-Guided Data Augmentation and NeRFs","publication_year":2024,"publication_date":"2024-04-08","ids":{"openalex":"https://openalex.org/W4394564202","doi":"https://doi.org/10.1109/lra.2024.3386053"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3386053","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2024.3386053","pdf_url":"https://ieeexplore.ieee.org/ielx7/7083369/7339444/10494375.pdf","source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/7083369/7339444/10494375.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102712548","display_name":"Andrea Tagliabue","orcid":"https://orcid.org/0000-0003-3376-4114"},"institutions":[{"id":"https://openalex.org/I4210143601","display_name":"Decision Systems (United States)","ror":"https://ror.org/0434dpa13","country_code":"US","type":"company","lineage":["https://openalex.org/I4210143601"]},{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrea Tagliabue","raw_affiliation_strings":["Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210143601","https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011665886","display_name":"Jonathan P. How","orcid":"https://orcid.org/0000-0001-8576-1930"},"institutions":[{"id":"https://openalex.org/I4210143601","display_name":"Decision Systems (United States)","ror":"https://ror.org/0434dpa13","country_code":"US","type":"company","lineage":["https://openalex.org/I4210143601"]},{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan P. How","raw_affiliation_strings":["Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210143601","https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102712548"],"corresponding_institution_ids":["https://openalex.org/I4210143601","https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":1.3108,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78996986,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"9","issue":"6","first_page":"5544","last_page":"5551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9959999918937683,"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":0.9959999918937683,"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/T10868","display_name":"Soft Robotics and Applications","score":0.9933000206947327,"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"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.982699990272522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6138649582862854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6123750805854797},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4524005651473999},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.45133736729621887},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.4246363639831543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37105852365493774},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.08513355255126953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6138649582862854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6123750805854797},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4524005651473999},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.45133736729621887},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.4246363639831543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37105852365493774},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.08513355255126953},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3386053","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2024.3386053","pdf_url":"https://ieeexplore.ieee.org/ielx7/7083369/7339444/10494375.pdf","source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/lra.2024.3386053","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2024.3386053","pdf_url":"https://ieeexplore.ieee.org/ielx7/7083369/7339444/10494375.pdf","source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4394564202.pdf","grobid_xml":"https://content.openalex.org/works/W4394564202.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1923344279","https://openalex.org/W1981723834","https://openalex.org/W1986014385","https://openalex.org/W1998058414","https://openalex.org/W2014549826","https://openalex.org/W2139362983","https://openalex.org/W2279098554","https://openalex.org/W2296673577","https://openalex.org/W2342840547","https://openalex.org/W2471962767","https://openalex.org/W2559336140","https://openalex.org/W2605102758","https://openalex.org/W2749680651","https://openalex.org/W2767050701","https://openalex.org/W2795837361","https://openalex.org/W2964070888","https://openalex.org/W2979863294","https://openalex.org/W2982095652","https://openalex.org/W3038825904","https://openalex.org/W3046559739","https://openalex.org/W3101442004","https://openalex.org/W3102552342","https://openalex.org/W3129860168","https://openalex.org/W3201459714","https://openalex.org/W3202883604","https://openalex.org/W3207397324","https://openalex.org/W3207977358","https://openalex.org/W4210985923","https://openalex.org/W4221151978","https://openalex.org/W4312313159","https://openalex.org/W4383097455","https://openalex.org/W4386076088","https://openalex.org/W6640174482","https://openalex.org/W6684338915","https://openalex.org/W6695314431","https://openalex.org/W6704559304","https://openalex.org/W6747311492"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Imitation":[0],"learning":[1,64,125],"(IL)":[2],"can":[3],"train":[4],"computationally-efficient":[5],"sensorimotor":[6],"policies":[7,171],"from":[8,137],"a":[9,37,54,122,126,156,175],"resource-intensive":[10],"model":[11],"predictive":[12],"controller":[13],"(MPC),":[14],"but":[15],"it":[16],"often":[17],"requires":[18],"many":[19],"samples,":[20],"leading":[21],"to":[22,81,98,103,113,174],"long":[23],"training":[24,163],"times":[25],"or":[26],"limited":[27],"robustness.":[28],"To":[29],"address":[30],"these":[31],"issues,":[32],"we":[33,52],"combine":[34],"IL":[35,167],"with":[36,185],"variant":[38],"of":[39,65,89,116,144,190],"robust":[40,91],"MPC":[41,92],"that":[42,59,131],"accounts":[43],"for":[44],"<italic":[45,61,66,94,127],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[46,62,67,95,128,158,196],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">process":[47],"and":[48,51,86,102,118,155],"sensing</i>":[49],"uncertainties,":[50],"design":[53],"data":[55],"augmentation":[56],"(DA)":[57],"strategy":[58],"enables":[60],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">efficient</i>":[63],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">vision-based</i>":[68],"policies.":[69],"The":[70],"proposed":[71],"DA":[72],"method,":[73],"named":[74],"Tube-NeRF,":[75],"leverages":[76],"Neural":[77],"Radiance":[78],"Fields":[79],"(NeRFs)":[80],"generate":[82],"novel":[83],"synthetic":[84],"images,":[85],"uses":[87],"properties":[88],"the":[90,106,114,138],"(the":[93],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">tube</i>":[96],")":[97],"select":[99],"relevant":[100],"views":[101],"efficiently":[104],"compute":[105],"corresponding":[107],"actions.":[108],"We":[109],"tailor":[110],"our":[111,170],"approach":[112],"task":[115],"localization":[117],"trajectory":[119],"tracking":[120,180],"on":[121],"multirotor,":[123,177],"by":[124],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">visuomotor</i>":[129],"policy":[130],"generates":[132],"control":[133],"actions":[134],"using":[135],"images":[136],"onboard":[139,187],"camera":[140],"as":[141],"only":[142,191],"source":[143],"horizontal":[145],"position.":[146],"Numerical":[147],"evaluations":[148],"show":[149],"80-fold":[150],"increase":[151],"in":[152,162],"demonstration":[153],"efficiency":[154],"<inline-formula":[157],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[159],"notation=\"LaTeX\">$50\\%$</tex-math></inline-formula>":[160],"reduction":[161],"time":[164,189],"over":[165],"current":[166],"methods.":[168],"Additionally,":[169],"successfully":[172],"transfer":[173],"real":[176],"achieving":[178],"low":[179],"errors":[181],"despite":[182],"large":[183],"disturbances,":[184],"an":[186],"inference":[188],"1.5":[192],"ms.":[193],"Video:":[194],"<uri":[195],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://youtu.be/8IzrcMxE7gE</uri>":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}