{"id":"https://openalex.org/W4312960604","doi":"https://doi.org/10.1109/iros47612.2022.9981866","title":"On the Importance of Label Encoding and Uncertainty Estimation for Robotic Grasp Detection","display_name":"On the Importance of Label Encoding and Uncertainty Estimation for Robotic Grasp Detection","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W4312960604","doi":"https://doi.org/10.1109/iros47612.2022.9981866"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9981866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981866","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5068815583","display_name":"Benedict Stephan","orcid":"https://orcid.org/0000-0001-5445-3935"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benedict Stephan","raw_affiliation_strings":["TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061677217","display_name":"Dustin Aganian","orcid":"https://orcid.org/0009-0006-3925-6718"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dustin Aganian","raw_affiliation_strings":["TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021075406","display_name":"Lars Hinneburg","orcid":null},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lars Hinneburg","raw_affiliation_strings":["TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101851750","display_name":"Markus Eisenbach","orcid":"https://orcid.org/0000-0003-4951-622X"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Markus Eisenbach","raw_affiliation_strings":["TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101950412","display_name":"Steffen M\u00fcller","orcid":"https://orcid.org/0000-0002-7831-7695"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Steffen M\u00fcller","raw_affiliation_strings":["TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075114390","display_name":"Horst\u2013Michael Gro\u00df","orcid":"https://orcid.org/0000-0001-9712-0225"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Horst-Michael Gross","raw_affiliation_strings":["TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Ilmenau,Neuroinformatics and Cognitive Robotics Lab,Ilmenau,Germany,98693","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I119449181"],"apc_list":null,"apc_paid":null,"fwci":1.7698,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85965998,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4781","last_page":"4788"},"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/T10868","display_name":"Soft Robotics and Applications","score":0.9634000062942505,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9264000058174133,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.9453102350234985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7682018876075745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6815910339355469},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6530605554580688},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5732617974281311},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5443394780158997},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.49238550662994385},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.46958938241004944},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4563922584056854},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43853816390037537},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.434144526720047},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.43204325437545776},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12125623226165771}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9453102350234985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7682018876075745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6815910339355469},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6530605554580688},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5732617974281311},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5443394780158997},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.49238550662994385},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.46958938241004944},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4563922584056854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43853816390037537},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.434144526720047},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.43204325437545776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12125623226165771},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9981866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981866","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G4215282625","display_name":null,"funder_award_id":"P2017-01-005","funder_id":"https://openalex.org/F4320309895","funder_display_name":"Carl-Zeiss-Stiftung"}],"funders":[{"id":"https://openalex.org/F4320309895","display_name":"Carl-Zeiss-Stiftung","ror":"https://ror.org/03ng4kg22"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W1579853615","https://openalex.org/W1999156278","https://openalex.org/W2140173255","https://openalex.org/W2205950488","https://openalex.org/W2600383743","https://openalex.org/W2824754393","https://openalex.org/W2889969363","https://openalex.org/W2953669419","https://openalex.org/W2962737955","https://openalex.org/W2962875890","https://openalex.org/W2963033241","https://openalex.org/W2967068439","https://openalex.org/W2986303149","https://openalex.org/W3004167188","https://openalex.org/W3035198432","https://openalex.org/W3105259478","https://openalex.org/W3130885760","https://openalex.org/W3132354223","https://openalex.org/W3186077919","https://openalex.org/W3205933337","https://openalex.org/W6617145748","https://openalex.org/W6735443497","https://openalex.org/W6749696961","https://openalex.org/W6888873376"],"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/W2562256921","https://openalex.org/W3102673927","https://openalex.org/W2327954668"],"abstract_inverted_index":{"Automated":[0],"grasping":[1],"of":[2,72,97,160,168,194,221],"arbitrary":[3],"objects":[4],"is":[5],"an":[6,144],"essential":[7],"skill":[8,26],"for":[9,27,66,127,146,214,223],"many":[10],"applications":[11],"such":[12],"as":[13,41],"smart":[14],"manufacturing":[15],"and":[16,43,80,107,172,188],"human":[17],"robot":[18],"interaction.":[19],"This":[20],"makes":[21],"grasp":[22,35,88,189,197,215,224],"detection":[23,36,89,216],"a":[24,82,109],"vital":[25],"automated":[28],"robotic":[29],"systems.":[30],"Recent":[31],"work":[32,48],"in":[33,226],"model-free":[34],"uses":[37],"point":[38],"cloud":[39],"data":[40],"input":[42],"typically":[44],"outperforms":[45],"the":[46,69,73,98,104,114,140,154,166,169,183,218],"earlier":[47],"on":[49,90,130,176],"RGB(D)-based":[50,55],"methods.":[51],"We":[52,163],"show":[53,95],"that":[54,85],"methods":[56,126],"are":[57,153],"being":[58],"underestimated":[59],"due":[60],"to":[61,156],"suboptimal":[62],"label":[63],"encodings":[64,79],"used":[65],"training.":[67],"Using":[68],"evaluation":[70],"pipeline":[71],"GraspNet-1Billion":[74,105],"dataset,":[75],"we":[76,94,123,137,152,181],"investigate":[77,165],"different":[78],"propose":[81,108],"novel":[83],"encoding":[84],"significantly":[86],"improves":[87],"depth":[91,207],"images.":[92],"Additionally,":[93,180],"shortcomings":[96],"2D":[99,227],"rectangle":[100],"grasps":[101],"supplied":[102],"by":[103,112],"dataset":[106],"filtering":[110],"scheme":[111],"which":[113],"ground":[115],"truth":[116],"labels":[117],"can":[118,138,209],"be":[119],"improved":[120],"significantly.":[121],"Furthermore,":[122],"apply":[124],"established":[125],"uncertainty":[128],"estimation":[129],"our":[131,203],"trained":[132],"models":[133],"since":[134],"knowing":[135],"when":[136],"trust":[139],"model's":[141],"decisions":[142],"provides":[143],"advantage":[145],"real-world":[147],"application.":[148],"By":[149,199],"doing":[150],"so,":[151],"first":[155],"directly":[157],"estimate":[158],"uncertainties":[159,174,187],"detected":[161],"grasps.":[162],"also":[164],"applicability":[167],"estimated":[170,186],"aleatoric":[171],"epistemic":[173],"based":[175],"their":[177],"theoretical":[178],"properties.":[179],"demonstrate":[182],"correlation":[184],"between":[185],"quality,":[190],"thus":[191],"improving":[192],"selection":[193],"high":[195],"quality":[196],"detections.":[198],"all":[200],"these":[201],"modifications,":[202],"approach":[204],"using":[205],"only":[206],"images":[208],"compete":[210],"with":[211],"point-cloud-based":[212],"approaches":[213],"despite":[217],"lower":[219],"degree":[220],"freedom":[222],"poses":[225],"image":[228],"space.":[229]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}