{"id":"https://openalex.org/W3092498085","doi":"https://doi.org/10.1109/case48305.2020.9216740","title":"Accelerating Grasp Exploration by Leveraging Learned Priors","display_name":"Accelerating Grasp Exploration by Leveraging Learned Priors","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3092498085","doi":"https://doi.org/10.1109/case48305.2020.9216740","mag":"3092498085"},"language":"en","primary_location":{"id":"doi:10.1109/case48305.2020.9216740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case48305.2020.9216740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","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/A5038043379","display_name":"Han Yu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153740","display_name":"Berkeley Systems (United States)","ror":"https://ror.org/05sb0mt20","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153740"]},{"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":"Han Yu Li","raw_affiliation_strings":["The AUTOLAB at UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The AUTOLAB at UC Berkeley","institution_ids":["https://openalex.org/I4210153740","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084920041","display_name":"Michael Danielczuk","orcid":"https://orcid.org/0000-0002-3858-2312"},"institutions":[{"id":"https://openalex.org/I4210153740","display_name":"Berkeley Systems (United States)","ror":"https://ror.org/05sb0mt20","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153740"]},{"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":"Michael Danielczuk","raw_affiliation_strings":["The AUTOLAB at UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The AUTOLAB at UC Berkeley","institution_ids":["https://openalex.org/I4210153740","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103260170","display_name":"Ashwin Balakrishna","orcid":"https://orcid.org/0000-0002-3508-7850"},"institutions":[{"id":"https://openalex.org/I4210153740","display_name":"Berkeley Systems (United States)","ror":"https://ror.org/05sb0mt20","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153740"]},{"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":"Ashwin Balakrishna","raw_affiliation_strings":["The AUTOLAB at UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The AUTOLAB at UC Berkeley","institution_ids":["https://openalex.org/I4210153740","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087111141","display_name":"Vishal Satish","orcid":"https://orcid.org/0000-0001-9544-6491"},"institutions":[{"id":"https://openalex.org/I4210153740","display_name":"Berkeley Systems (United States)","ror":"https://ror.org/05sb0mt20","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153740"]},{"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":"Vishal Satish","raw_affiliation_strings":["The AUTOLAB at UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The AUTOLAB at UC Berkeley","institution_ids":["https://openalex.org/I4210153740","https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050342525","display_name":"Ken Goldberg","orcid":"https://orcid.org/0000-0002-2661-4524"},"institutions":[{"id":"https://openalex.org/I4210153740","display_name":"Berkeley Systems (United States)","ror":"https://ror.org/05sb0mt20","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153740"]},{"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":"Ken Goldberg","raw_affiliation_strings":["The AUTOLAB at UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The AUTOLAB at UC Berkeley","institution_ids":["https://openalex.org/I4210153740","https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9940999746322632,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9715999960899353,"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/grasp","display_name":"GRASP","score":0.958397626876831},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.724650502204895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7197428941726685},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.666549801826477},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6301814317703247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.625868558883667},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5420771837234497},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5382452011108398},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5334475636482239},{"id":"https://openalex.org/keywords/planner","display_name":"Planner","score":0.466146856546402},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4388253688812256},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42182090878486633},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40001511573791504},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.17683687806129456}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.958397626876831},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.724650502204895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7197428941726685},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.666549801826477},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6301814317703247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.625868558883667},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5420771837234497},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5382452011108398},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5334475636482239},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.466146856546402},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4388253688812256},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42182090878486633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40001511573791504},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.17683687806129456},{"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/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case48305.2020.9216740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case48305.2020.9216740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1503925285","https://openalex.org/W1564897360","https://openalex.org/W1651456183","https://openalex.org/W1820657498","https://openalex.org/W1979354511","https://openalex.org/W1985514943","https://openalex.org/W1999156278","https://openalex.org/W2036637075","https://openalex.org/W2041376653","https://openalex.org/W2108738385","https://openalex.org/W2201912979","https://openalex.org/W2414685554","https://openalex.org/W2485911221","https://openalex.org/W2600030077","https://openalex.org/W2626073992","https://openalex.org/W2810785043","https://openalex.org/W2910474428","https://openalex.org/W2962736495","https://openalex.org/W2962899390","https://openalex.org/W2963033241","https://openalex.org/W2963390419","https://openalex.org/W2964239605","https://openalex.org/W2974428228","https://openalex.org/W2977786941","https://openalex.org/W3004954647","https://openalex.org/W3010515602","https://openalex.org/W3039599385","https://openalex.org/W3103768745","https://openalex.org/W3112422759","https://openalex.org/W4239181501","https://openalex.org/W4244404253","https://openalex.org/W6676077707","https://openalex.org/W6735571901","https://openalex.org/W6739378191","https://openalex.org/W6753243525","https://openalex.org/W6785691520"],"related_works":["https://openalex.org/W2163296013","https://openalex.org/W2743859443","https://openalex.org/W2326995835","https://openalex.org/W165915117","https://openalex.org/W2059402478","https://openalex.org/W2123347777","https://openalex.org/W4387804363","https://openalex.org/W2019547100","https://openalex.org/W2477150073","https://openalex.org/W2515493494"],"abstract_inverted_index":{"The":[0,71],"ability":[1],"of":[2,48,91,98,145,159],"robots":[3],"to":[4,37,60,83,114],"grasp":[5,38,61,81,85,92],"novel":[6,100],"objects":[7,39],"has":[8],"industry":[9],"applications":[10],"in":[11,24],"e-commerce":[12],"order":[13],"fulfillment":[14],"and":[15,87,141],"home":[16],"service.":[17],"Data-driven":[18],"grasping":[19,29],"policies":[20],"have":[21,41],"achieved":[22],"success":[23,93],"learning":[25],"general":[26],"strategies":[27],"for":[28,94],"arbitrary":[30],"objects.":[31,122],"However,":[32],"these":[33,121],"approaches":[34],"can":[35],"fail":[36],"which":[40],"complex":[42],"geometry":[43,67],"or":[44],"are":[45],"significantly":[46],"outside":[47],"the":[49,77,99,106,109,126],"training":[50,154],"distribution.":[51],"We":[52,102],"present":[53],"a":[54,62,138,157],"Thompson":[55],"sampling":[56],"algorithm":[57,72],"that":[58,104,125],"learns":[59],"given":[63],"object":[64,161],"with":[65,108],"unknown":[66],"using":[68],"online":[69],"experience.":[70],"leverages":[73],"learned":[74,128],"priors":[75],"from":[76],"Dexterity":[78],"Network":[79],"robot":[80],"planner":[82],"guide":[84],"exploration":[86],"provide":[88],"probabilistic":[89],"estimates":[90],"each":[95],"stable":[96],"pose":[97],"object.":[101],"find":[103,117],"seeding":[105],"policy":[107,129],"Dex-Net":[110],"prior":[111],"allows":[112],"it":[113],"more":[115],"efficiently":[116],"robust":[118],"grasps":[119],"on":[120],"Experiments":[123],"suggest":[124],"best":[127],"attains":[130],"an":[131,146],"average":[132],"total":[133],"reward":[134],"64.5%":[135],"higher":[136],"than":[137],"greedy":[139],"baseline":[140,148],"achieves":[142],"within":[143],"5.7%":[144],"oracle":[147],"when":[149],"evaluated":[150],"over":[151],"300,":[152],"000":[153],"runs":[155],"across":[156],"set":[158],"3000":[160],"poses.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
