{"id":"https://openalex.org/W2766108544","doi":"https://doi.org/10.1109/iros.2018.8593933","title":"Domain Randomization and Generative Models for Robotic Grasping","display_name":"Domain Randomization and Generative Models for Robotic Grasping","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2766108544","doi":"https://doi.org/10.1109/iros.2018.8593933","mag":"2766108544"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2018.8593933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2018.8593933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/1710.06425","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012812463","display_name":"Joshua Tobin","orcid":null},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Josh Tobin","raw_affiliation_strings":["UC Berkeley"],"affiliations":[{"raw_affiliation_string":"UC Berkeley","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003685124","display_name":"Lukas Biewald","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lukas Biewald","raw_affiliation_strings":["Weights and Biases, Inc"],"affiliations":[{"raw_affiliation_string":"Weights and Biases, Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036908757","display_name":"Rocky Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rocky Duan","raw_affiliation_strings":["Embodied Intelligence"],"affiliations":[{"raw_affiliation_string":"Embodied Intelligence","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091819924","display_name":"Marcin Andrychowicz","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161460","display_name":"OpenAI (United States)","ror":"https://ror.org/05wx9n238","country_code":"US","type":"company","lineage":["https://openalex.org/I4210161460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marcin Andrychowicz","raw_affiliation_strings":["OpenAI"],"affiliations":[{"raw_affiliation_string":"OpenAI","institution_ids":["https://openalex.org/I4210161460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055942061","display_name":"Ankur Handa","orcid":"https://orcid.org/0000-0001-5170-1323"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ankur Handa","raw_affiliation_strings":["NVIDIA"],"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101582318","display_name":"Vikash Kumar","orcid":"https://orcid.org/0000-0001-6422-6066"},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vikash Kumar","raw_affiliation_strings":["UC Berkeley"],"affiliations":[{"raw_affiliation_string":"UC Berkeley","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026829243","display_name":"Bob McGrew","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161460","display_name":"OpenAI (United States)","ror":"https://ror.org/05wx9n238","country_code":"US","type":"company","lineage":["https://openalex.org/I4210161460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bob McGrew","raw_affiliation_strings":["OpenAI"],"affiliations":[{"raw_affiliation_string":"OpenAI","institution_ids":["https://openalex.org/I4210161460"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Alex Ray","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161460","display_name":"OpenAI (United States)","ror":"https://ror.org/05wx9n238","country_code":"US","type":"company","lineage":["https://openalex.org/I4210161460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alex Ray","raw_affiliation_strings":["OpenAI"],"affiliations":[{"raw_affiliation_string":"OpenAI","institution_ids":["https://openalex.org/I4210161460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113782851","display_name":"Jonas Schneider","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161460","display_name":"OpenAI (United States)","ror":"https://ror.org/05wx9n238","country_code":"US","type":"company","lineage":["https://openalex.org/I4210161460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonas Schneider","raw_affiliation_strings":["OpenAI"],"affiliations":[{"raw_affiliation_string":"OpenAI","institution_ids":["https://openalex.org/I4210161460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010674841","display_name":"Peter Welinder","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161460","display_name":"OpenAI (United States)","ror":"https://ror.org/05wx9n238","country_code":"US","type":"company","lineage":["https://openalex.org/I4210161460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Welinder","raw_affiliation_strings":["OpenAI"],"affiliations":[{"raw_affiliation_string":"OpenAI","institution_ids":["https://openalex.org/I4210161460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076651586","display_name":"Wojciech Zaremba","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161460","display_name":"OpenAI (United States)","ror":"https://ror.org/05wx9n238","country_code":"US","type":"company","lineage":["https://openalex.org/I4210161460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wojciech Zaremba","raw_affiliation_strings":["OpenAI"],"affiliations":[{"raw_affiliation_string":"OpenAI","institution_ids":["https://openalex.org/I4210161460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049349154","display_name":"Pieter Abbeel","orcid":null},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pieter Abbeel","raw_affiliation_strings":["UC Berkeley"],"affiliations":[{"raw_affiliation_string":"UC Berkeley","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":12,"corresponding_author_ids":["https://openalex.org/A5012812463"],"corresponding_institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":3.5539,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.93057989,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3482","last_page":"3489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9729999899864197,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9718999862670898,"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/grasp","display_name":"GRASP","score":0.8300684690475464},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7223501205444336},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6956841945648193},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6212792992591858},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5946280360221863},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5445722341537476},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5435663461685181},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5045784711837769},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4803670346736908},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4482755661010742},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.426631361246109},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2522289752960205}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.8300684690475464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7223501205444336},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6956841945648193},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6212792992591858},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5946280360221863},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5445722341537476},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5435663461685181},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5045784711837769},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4803670346736908},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4482755661010742},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.426631361246109},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2522289752960205},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iros.2018.8593933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2018.8593933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1710.06425","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1710.06425","pdf_url":"https://arxiv.org/pdf/1710.06425","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":"","raw_type":"text"},{"id":"mag:2766108544","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1710.06425","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.1710.06425","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1710.06425","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1710.06425","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1710.06425","pdf_url":"https://arxiv.org/pdf/1710.06425","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":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2766108544.pdf","grobid_xml":"https://content.openalex.org/works/W2766108544.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W70651934","https://openalex.org/W1505952289","https://openalex.org/W1510186039","https://openalex.org/W1522301498","https://openalex.org/W1564897360","https://openalex.org/W1820657498","https://openalex.org/W1949568868","https://openalex.org/W1969868017","https://openalex.org/W1977023370","https://openalex.org/W1981667747","https://openalex.org/W1986533639","https://openalex.org/W1999156278","https://openalex.org/W2005824379","https://openalex.org/W2025612888","https://openalex.org/W2033223309","https://openalex.org/W2036637075","https://openalex.org/W2041376653","https://openalex.org/W2072890037","https://openalex.org/W2088043683","https://openalex.org/W2106628124","https://openalex.org/W2118262422","https://openalex.org/W2125549624","https://openalex.org/W2135181320","https://openalex.org/W2140173255","https://openalex.org/W2155217025","https://openalex.org/W2156219259","https://openalex.org/W2157006255","https://openalex.org/W2158782408","https://openalex.org/W2161719807","https://openalex.org/W2169241897","https://openalex.org/W2190691619","https://openalex.org/W2205975260","https://openalex.org/W2423557781","https://openalex.org/W2485911221","https://openalex.org/W2517300719","https://openalex.org/W2528973876","https://openalex.org/W2565902248","https://openalex.org/W2600030077","https://openalex.org/W2605102758","https://openalex.org/W2615555567","https://openalex.org/W2626073992","https://openalex.org/W2745471877","https://openalex.org/W2754340109","https://openalex.org/W2754950076","https://openalex.org/W2771865340","https://openalex.org/W2805278171","https://openalex.org/W2949379496","https://openalex.org/W2949382160","https://openalex.org/W2949595773","https://openalex.org/W2952606116","https://openalex.org/W2952838738","https://openalex.org/W2953249127","https://openalex.org/W2953318193","https://openalex.org/W2962736495","https://openalex.org/W2962899390","https://openalex.org/W2963678509","https://openalex.org/W2964239605","https://openalex.org/W4244404253","https://openalex.org/W6639317949","https://openalex.org/W6680498451","https://openalex.org/W6683240801","https://openalex.org/W6684191040","https://openalex.org/W6684916627","https://openalex.org/W6697071109"],"related_works":["https://openalex.org/W2964214518","https://openalex.org/W2973454014","https://openalex.org/W2903364556","https://openalex.org/W2161047498","https://openalex.org/W3101442004","https://openalex.org/W2962899390","https://openalex.org/W2962736495","https://openalex.org/W2083181129","https://openalex.org/W3204858942","https://openalex.org/W3157546242","https://openalex.org/W3206209837","https://openalex.org/W2556722685","https://openalex.org/W3209254063","https://openalex.org/W3151839396","https://openalex.org/W2968410673","https://openalex.org/W2959735980","https://openalex.org/W2296180239","https://openalex.org/W2951738103","https://openalex.org/W3158779221","https://openalex.org/W2949408529"],"abstract_inverted_index":{"Deep":[0],"learning-based":[1],"robotic":[2],"grasping":[3],"has":[4],"made":[5],"significant":[6],"progress":[7],"thanks":[8],"to":[9,58,69,87,122,133],"algorithmic":[10],"improvements":[11],"and":[12,33,81,149,155],"increased":[13],"data":[14,49,150],"availability.":[15],"However,":[16],"state-of-the-art":[17],"models":[18],"are":[19],"often":[20],"trained":[21,182,201],"on":[22,91,168,183,193,202],"as":[23,25,34],"few":[24],"hundreds":[26],"or":[27],"thousands":[28],"of":[29,66,75,97,119],"unique":[30],"object":[31,70,103],"instances,":[32],"a":[35,40,47,54,83,101,120,123,164],"result":[36],"generalization":[37],"can":[38,104,162],"be":[39,105],"challenge.":[41],"In":[42],"this":[43],"work,":[44],"we":[45,108,161],"explore":[46],"novel":[48],"generation":[50,151],"pipeline":[51,152],"for":[52,100],"training":[53],"deep":[55,84],"neural":[56,85],"network":[57,86],"perform":[59,88],"grasp":[60,89,112,195],"planning":[61,90,113],"that":[62,115],"applies":[63],"the":[64,95,156],"idea":[65],"domain":[67],"randomization":[68],"synthesis.":[71],"We":[72,144,159,186],"generate":[73],"millions":[74],"unique,":[76],"unrealistic":[77],"procedurally":[78],"generated":[79],"objects,":[80],"train":[82],"these":[92],"objects.":[93,185,205],"Since":[94],"distribution":[96,125],"successful":[98],"grasps":[99,135],"given":[102],"highly":[106],"multimodal,":[107],"propose":[109],"an":[110,189],"autoregressive":[111],"model":[114,130,147],"maps":[116],"sensor":[117],"inputs":[118],"scene":[121],"probability":[124],"over":[126],"possible":[127],"grasps.":[128],"This":[129],"allows":[131],"us":[132],"sample":[134],"efficiently":[136],"at":[137,173],"test":[138,174],"time":[139,175],"(or":[140],"avoid":[141],"sampling":[142],"entirely).":[143],"evaluate":[145],"our":[146],"architecture":[148],"in":[153,176],"simulation":[154,177],"real":[157],"world.":[158],"find":[160],"achieve":[163],">90%":[165],"success":[166,191],"rate":[167,192],"previously":[169],"unseen":[170],"realistic":[171],"objects":[172],"despite":[178,197],"having":[179,198],"only":[180,199],"been":[181,200],"random":[184,203],"also":[187],"demonstrate":[188],"80%":[190],"real-world":[194],"attempts":[196],"simulated":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1}],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}
