{"id":"https://openalex.org/W2932428296","doi":"https://doi.org/10.1109/hri.2019.8673019","title":"SAIL: Simulation-Informed Active In-the-Wild Learning","display_name":"SAIL: Simulation-Informed Active In-the-Wild Learning","publication_year":2019,"publication_date":"2019-03-01","ids":{"openalex":"https://openalex.org/W2932428296","doi":"https://doi.org/10.1109/hri.2019.8673019","mag":"2932428296"},"language":"en","primary_location":{"id":"doi:10.1109/hri.2019.8673019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hri.2019.8673019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)","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/A5077011363","display_name":"Elaine Schaertl Short","orcid":"https://orcid.org/0000-0002-4789-9979"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Elaine Schaertl Short","raw_affiliation_strings":["Dept. of Electrical and Computer Eng., University of Texas at Austin, Austin, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Eng., University of Texas at Austin, Austin, Texas, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011415195","display_name":"Adam Allevato","orcid":"https://orcid.org/0000-0001-8795-1498"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam Allevato","raw_affiliation_strings":["Dept. of Mechanical Eng., University of Texas at Austin, Austin, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Mechanical Eng., University of Texas at Austin, Austin, Texas, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066797327","display_name":"Andrea L. Thomaz","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea L. Thomaz","raw_affiliation_strings":["Dept. of Electrical and Computer Eng., University of Texas at Austin, Austin, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Eng., University of Texas at Austin, Austin, Texas, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077011363"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":0.8316,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.72759809,"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":"468","last_page":"477"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9994000196456909,"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":0.9994000196456909,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9975000023841858,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9898999929428101,"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":0.7583544254302979},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7533059120178223},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.7470868825912476},{"id":"https://openalex.org/keywords/supervisor","display_name":"Supervisor","score":0.6777654886245728},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6186785101890564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6064296960830688},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.539328932762146},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46073099970817566},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.45379698276519775},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.45288538932800293},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.42990708351135254},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.42557400465011597},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09134912490844727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7583544254302979},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7533059120178223},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.7470868825912476},{"id":"https://openalex.org/C2779110517","wikidata":"https://www.wikidata.org/wiki/Q1240788","display_name":"Supervisor","level":2,"score":0.6777654886245728},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6186785101890564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6064296960830688},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.539328932762146},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46073099970817566},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.45379698276519775},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.45288538932800293},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.42990708351135254},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.42557400465011597},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09134912490844727},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hri.2019.8673019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hri.2019.8673019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)","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":39,"referenced_works":["https://openalex.org/W206243501","https://openalex.org/W1541317966","https://openalex.org/W2005142267","https://openalex.org/W2070707168","https://openalex.org/W2078158966","https://openalex.org/W2081034428","https://openalex.org/W2094387729","https://openalex.org/W2098441518","https://openalex.org/W2132322793","https://openalex.org/W2156737235","https://openalex.org/W2156869222","https://openalex.org/W2158582431","https://openalex.org/W2171054284","https://openalex.org/W2181594852","https://openalex.org/W2294422333","https://openalex.org/W2342968705","https://openalex.org/W2556090351","https://openalex.org/W2621205314","https://openalex.org/W2725263144","https://openalex.org/W2736629007","https://openalex.org/W2737944367","https://openalex.org/W2741122588","https://openalex.org/W2764902300","https://openalex.org/W2774277131","https://openalex.org/W2792089292","https://openalex.org/W2962736495","https://openalex.org/W2964263543","https://openalex.org/W2964273112","https://openalex.org/W3142030220","https://openalex.org/W4245685249","https://openalex.org/W4295264289","https://openalex.org/W4321392130","https://openalex.org/W6668103157","https://openalex.org/W6674812091","https://openalex.org/W6683195989","https://openalex.org/W6696972564","https://openalex.org/W6697071109","https://openalex.org/W6738860160","https://openalex.org/W6739585900"],"related_works":["https://openalex.org/W4387731985","https://openalex.org/W2755149878","https://openalex.org/W2941808082","https://openalex.org/W2468425257","https://openalex.org/W4377009725","https://openalex.org/W4379086698","https://openalex.org/W2528721242","https://openalex.org/W4320164562","https://openalex.org/W2356364326","https://openalex.org/W2967461658"],"abstract_inverted_index":{"Robots":[0],"in":[1,11,99,138,152,180,189],"real-world":[2],"environments":[3,16],"may":[4,33,45],"need":[5],"to":[6,14,39,51,71,88,108,110,121,158,172,200,204],"adapt":[7],"context-specific":[8],"behaviors":[9],"learned":[10],"one":[12],"environment":[13],"new":[15,18,69,90,123],"with":[17,29],"constraints.":[19],"In":[20,55,79],"many":[21],"cases,":[22],"copresent":[23],"humans":[24,112],"can":[25,169],"provide":[26,40,52],"the":[27,60,83,100,153,190,197,211],"robot":[28,84,120],"information,":[30],"but":[31],"it":[32],"not":[34,46],"be":[35,47,170],"safe":[36],"for":[37,67],"them":[38],"hands-on":[41],"demonstrations":[42],"and":[43,103,113,146,177],"there":[44],"a":[48,76,119,139,181],"dedicated":[49],"supervisor":[50],"constant":[53],"feedback.":[54],"this":[56,80],"work":[57],"we":[58],"present":[59],"SAIL":[61],"(Simulation-Informed":[62],"Active":[63],"In-the-Wild":[64],"Learning)":[65],"algorithm":[66],"learning":[68],"approaches":[70],"manipulation":[72,144],"skills":[73],"starting":[74],"from":[75,135,150],"single":[77],"demonstration.":[78],"three-step":[81],"algorithm,":[82],"simulates":[85],"task":[86,97,183],"execution":[87,98],"choose":[89,201],"potential":[91],"approaches;":[92],"collects":[93],"unsupervised":[94],"data":[95,168,199],"on":[96],"target":[101],"environment;":[102],"finally,":[104],"chooses":[105],"informative":[106],"actions":[107,145,203],"show":[109,162,194],"co-present":[111],"obtain":[114],"labels.":[115],"Our":[116],"approach":[117],"enables":[118],"learn":[122],"ways":[124],"of":[125],"executing":[126],"two":[127],"different":[128],"tasks":[129],"by":[130],"using":[131,196],"success/failure":[132],"labels":[133,149],"obtained":[134],"na\u00efve":[136],"users":[137,151],"public":[140],"space,":[141],"performing":[142],"496":[143],"collecting":[147],"163":[148],"wild":[154],"over":[155],"six":[156],"45-minute":[157],"1-hour":[159],"deployments.":[160],"We":[161,192],"that":[163,195],"classifiers":[164],"based":[165],"low-level":[166],"sensor":[167,198],"used":[171],"accurately":[173],"distinguish":[174],"between":[175],"successful":[176],"unsuccessful":[178],"motions":[179],"multi-step":[182],"(":[184],"),":[185],"even":[186],"when":[187],"trained":[188],"wild.":[191],"also":[193],"which":[202],"sample":[205],"is":[206],"more":[207],"effective":[208],"than":[209],"choosing":[210],"least-sampled":[212],"action.":[213]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}