{"id":"https://openalex.org/W1503925285","doi":"https://doi.org/10.1109/icra.2015.7139793","title":"Leveraging big data for grasp planning","display_name":"Leveraging big data for grasp planning","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1503925285","doi":"https://doi.org/10.1109/icra.2015.7139793","mag":"1503925285"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2015.7139793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2015.7139793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Robotics and Automation (ICRA)","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/A5039293409","display_name":"Daniel Kappler","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Kappler","raw_affiliation_strings":["Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems, T\u00fcbingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021676288","display_name":"Jeannette Bohg","orcid":"https://orcid.org/0000-0002-4921-7193"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jeannette Bohg","raw_affiliation_strings":["Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems, T\u00fcbingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029642293","display_name":"Stefan Schaal","orcid":"https://orcid.org/0000-0001-5660-1874"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Stefan Schaal","raw_affiliation_strings":["Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems, T\u00fcbingen, Germany","Computational Learning and Motor Control lab at the University of Southern California, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I4210135521"]},{"raw_affiliation_string":"Computational Learning and Motor Control lab at the University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":283,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4304","last_page":"4311"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9991000294685364,"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":0.9991000294685364,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9613000154495239,"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":0.9516000151634216,"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":0.9443085193634033},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7231591939926147},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6928090453147888},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6718177795410156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5743737816810608},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.521884024143219},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5107414722442627},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4745802879333496},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4595462679862976},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4409427046775818},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36617374420166016},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09333604574203491}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9443085193634033},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7231591939926147},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6928090453147888},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6718177795410156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5743737816810608},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.521884024143219},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5107414722442627},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4745802879333496},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4595462679862976},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4409427046775818},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36617374420166016},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09333604574203491},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra.2015.7139793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2015.7139793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.mpg.de:item_2259825","is_oa":false,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-002A-1FD1-E","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the IEEE International Conference on Robotics and Automation","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W46565623","https://openalex.org/W1663973292","https://openalex.org/W1794703952","https://openalex.org/W1968565040","https://openalex.org/W1980602022","https://openalex.org/W1983615882","https://openalex.org/W1999156278","https://openalex.org/W2002333927","https://openalex.org/W2008073424","https://openalex.org/W2021683594","https://openalex.org/W2023135124","https://openalex.org/W2041376653","https://openalex.org/W2042599225","https://openalex.org/W2057299504","https://openalex.org/W2060698516","https://openalex.org/W2063189785","https://openalex.org/W2072128103","https://openalex.org/W2085949256","https://openalex.org/W2088043683","https://openalex.org/W2106638738","https://openalex.org/W2108598243","https://openalex.org/W2112645080","https://openalex.org/W2117130368","https://openalex.org/W2125549624","https://openalex.org/W2126496149","https://openalex.org/W2128621978","https://openalex.org/W2138857742","https://openalex.org/W2160609165","https://openalex.org/W2162000109","https://openalex.org/W2162160008","https://openalex.org/W2295343990","https://openalex.org/W2606321545","https://openalex.org/W2655987061","https://openalex.org/W2983963859","https://openalex.org/W3112422759","https://openalex.org/W3148347377","https://openalex.org/W4231109964","https://openalex.org/W6650115879","https://openalex.org/W6652231383","https://openalex.org/W6672186150","https://openalex.org/W6676115828","https://openalex.org/W6680300913","https://openalex.org/W6740091750","https://openalex.org/W6769537543"],"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/W4390800284"],"abstract_inverted_index":{"We":[0,34,61,142],"propose":[1],"a":[2,12,36,57,89,144,189],"new":[3],"large-scale":[4,156],"database":[5,157],"containing":[6],"grasps":[7,21],"that":[8,81,106,129,150,171],"are":[9,22,27,109,177],"applied":[10],"to":[11,64,124,134,164,188],"large":[13],"set":[14],"of":[15,41,68,160],"objects":[16],"from":[17,182],"numerous":[18],"categories.":[19],"These":[20],"generated":[23],"in":[24,127,137],"simulation":[25,87,128],"and":[26,38,148,185],"annotated":[28],"with":[29,71],"different":[30],"grasp":[31,49,72,94,116,161],"stability":[32],"metrics.":[33],"use":[35,62],"descriptive":[37],"efficient":[39],"representation":[40],"the":[42,66,69,82,97,104,119,138,155,168,175,183],"local":[43],"object":[44],"shape":[45],"at":[46],"which":[47],"each":[48],"is":[50,88],"applied.":[51],"Given":[52],"this":[53],"data,":[54],"we":[55],"present":[56],"two-fold":[58],"analysis:":[59],"(i)":[60],"crowdsourcing":[63],"analyze":[65],"correlation":[67],"metrics":[70],"success":[73,95,162],"as":[74],"predicted":[75],"by":[76],"humans.":[77],"The":[78,100],"results":[79,101,169],"show":[80,149],"metric":[83],"based":[84,173],"on":[85,174],"physics":[86],"more":[90],"consistent":[91],"predictor":[92],"for":[93,112,158],"than":[96,180],"standard":[98],"\u03c5-metric.":[99],"also":[102],"support":[103],"hypothesis":[105],"human":[107],"labels":[108,172],"not":[110],"required":[111],"good":[113],"ground":[114],"truth":[115],"data.":[117],"Instead":[118],"physics-metric":[120,176],"can":[121,152],"be":[122,132],"used":[123,133],"generate":[125],"datasets":[126],"may":[130],"then":[131],"bootstrap":[135],"learning":[136,146],"real":[139],"world.":[140],"(ii)":[141],"apply":[143],"deep":[145],"method":[147],"it":[151],"better":[153,190],"leverage":[154],"prediction":[159],"compared":[163],"logistic":[165],"regression.":[166],"Furthermore,":[167],"suggest":[170],"less":[178],"noisy":[179],"those":[181],"\u03c5-metric":[184],"therefore":[186],"lead":[187],"classification":[191],"performance.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":34},{"year":2020,"cited_by_count":44},{"year":2019,"cited_by_count":37},{"year":2018,"cited_by_count":26},{"year":2017,"cited_by_count":31},{"year":2016,"cited_by_count":20},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}