{"id":"https://openalex.org/W3003686473","doi":"https://doi.org/10.1109/iros40897.2019.8967958","title":"Partial Caging: A Clearance-Based Definition and Deep Learning","display_name":"Partial Caging: A Clearance-Based Definition and Deep Learning","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3003686473","doi":"https://doi.org/10.1109/iros40897.2019.8967958","mag":"3003686473"},"language":"en","primary_location":{"id":"doi:10.1109/iros40897.2019.8967958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8967958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5010206538","display_name":"Anastasiia Varava","orcid":"https://orcid.org/0000-0002-0900-1523"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Anastasiia Varava","raw_affiliation_strings":["KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","institution_ids":["https://openalex.org/I86987016"]},{"raw_affiliation_string":"Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020344044","display_name":"Michael C. Welle","orcid":"https://orcid.org/0000-0003-3827-3824"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Michael C. Welle","raw_affiliation_strings":["KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","institution_ids":["https://openalex.org/I86987016"]},{"raw_affiliation_string":"Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020901032","display_name":"Jeffrey Mahler","orcid":"https://orcid.org/0000-0003-3204-3024"},"institutions":[{"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"]},{"id":"https://openalex.org/I73544541","display_name":"Mathematical Sciences Research Institute","ror":"https://ror.org/05hs5r386","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I73544541"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeffrey Mahler","raw_affiliation_strings":["University of California,AUTOLab, Department of Electrical Engineenng and Computer Science,Berkeley","AUTOLab, Department of Electrical Engineenng and Computer Science, University of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"University of California,AUTOLab, Department of Electrical Engineenng and Computer Science,Berkeley","institution_ids":["https://openalex.org/I73544541"]},{"raw_affiliation_string":"AUTOLab, Department of Electrical Engineenng and Computer Science, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050342525","display_name":"Ken Goldberg","orcid":"https://orcid.org/0000-0002-2661-4524"},"institutions":[{"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"]},{"id":"https://openalex.org/I73544541","display_name":"Mathematical Sciences Research Institute","ror":"https://ror.org/05hs5r386","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I73544541"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ken Goldberg","raw_affiliation_strings":["University of California,AUTOLab, Department of Electrical Engineenng and Computer Science,Berkeley","AUTOLab, Department of Electrical Engineenng and Computer Science, University of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"University of California,AUTOLab, Department of Electrical Engineenng and Computer Science,Berkeley","institution_ids":["https://openalex.org/I73544541"]},{"raw_affiliation_string":"AUTOLab, Department of Electrical Engineenng and Computer Science, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023792180","display_name":"Danica Kragi\u0107","orcid":"https://orcid.org/0000-0003-2965-2953"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Danica Kragic","raw_affiliation_strings":["KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","institution_ids":["https://openalex.org/I86987016"]},{"raw_affiliation_string":"Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053916652","display_name":"Florian T. Pokomy","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Florian T. Pokomy","raw_affiliation_strings":["KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of technology varavar,Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science","institution_ids":["https://openalex.org/I86987016"]},{"raw_affiliation_string":"Division of Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, KTH Royal Institute of technology varavar","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5010206538"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.4989,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67480332,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1533","last_page":"1540"},"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":0.984000027179718,"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/T11799","display_name":"Adhesion, Friction, and Surface Interactions","score":0.9465000033378601,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7496378421783447},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6995417475700378},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.630404531955719},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6026248931884766},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5545687079429626},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.5230332612991333},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4586202800273895},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4472280740737915},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4440232217311859},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4288172721862793},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.42359936237335205},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42186814546585083},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4148842692375183},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41279205679893494},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39069104194641113},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1483575403690338},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10029497742652893}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7496378421783447},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6995417475700378},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.630404531955719},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6026248931884766},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5545687079429626},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.5230332612991333},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4586202800273895},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4472280740737915},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4440232217311859},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4288172721862793},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.42359936237335205},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42186814546585083},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4148842692375183},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41279205679893494},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39069104194641113},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1483575403690338},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10029497742652893},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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":1,"locations":[{"id":"doi:10.1109/iros40897.2019.8967958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8967958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/W1503925285","https://openalex.org/W1820657498","https://openalex.org/W1981667747","https://openalex.org/W1999156278","https://openalex.org/W2000638494","https://openalex.org/W2025848827","https://openalex.org/W2029909232","https://openalex.org/W2041376653","https://openalex.org/W2051725602","https://openalex.org/W2064097161","https://openalex.org/W2065736001","https://openalex.org/W2068375174","https://openalex.org/W2097117768","https://openalex.org/W2104811860","https://openalex.org/W2113643677","https://openalex.org/W2114306020","https://openalex.org/W2136981968","https://openalex.org/W2201912979","https://openalex.org/W2289299303","https://openalex.org/W2402144811","https://openalex.org/W2485911221","https://openalex.org/W2521265935","https://openalex.org/W2550858736","https://openalex.org/W2600030077","https://openalex.org/W2773721443","https://openalex.org/W2803196488","https://openalex.org/W2810785043","https://openalex.org/W2953249127","https://openalex.org/W2953384591","https://openalex.org/W2962736495","https://openalex.org/W2962746398","https://openalex.org/W2962899390","https://openalex.org/W2963654160","https://openalex.org/W2964121744","https://openalex.org/W2989259058","https://openalex.org/W6713134421","https://openalex.org/W6744542307","https://openalex.org/W6746713385","https://openalex.org/W6753243525"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W3013085049","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Caging":[0],"grasps":[1],"limit":[2],"the":[3,104,141,171,176,179,200,216,219],"mobility":[4],"of":[5,12,19,27,69,106,111,114,163,178,208,218,232],"an":[6,28],"object":[7,70],"to":[8,82,102,126,186],"a":[9,17,34,40,45,57,93,160,233,237],"bounded":[10],"component":[11],"configuration":[13,235],"space.":[14],"We":[15,49],"introduce":[16],"notion":[18],"partial":[20,61,90],"cage":[21,62,220],"quality":[22,63,105,221],"based":[23],"on":[24,132,146,175,236],"maximal":[25],"clearance":[26],"escaping":[29],"path.":[30],"As":[31],"this":[32],"is":[33,80,100,124],"computationally":[35],"demanding":[36],"task":[37],"even":[38],"in":[39],"two-dimensional":[41],"scenario,":[42],"we":[43,97,168,197,214],"propose":[44],"deep":[46],"learning":[47],"approach.":[48],"design":[50],"two":[51],"convolutional":[52],"neural":[53,77],"networks":[54,131,142],"and":[55,72,116,128,136,151,213],"construct":[56],"pipeline":[58,202],"for":[59,148],"real-time":[60],"estimation":[64],"directly":[65],"from":[66],"2D":[67],"images":[68,113],"models":[71],"planar":[73],"caging":[74,84,121,137,153,210,225],"tools.":[75],"One":[76],"network,":[78],"CageMaskNN,":[79],"used":[81,125],"identify":[83,205],"tool":[85,122,138,154,211,226],"locations":[86],"that":[87,96,199,230],"can":[88,203],"support":[89],"cages,":[91],"while":[92],"second":[94],"network":[95],"call":[98],"CageClearanceNN":[99],"trained":[101,144],"predict":[103],"those":[107],"configurations.":[108,139],"A":[109],"dataset":[110],"3811":[112],"objects":[115,135],"more":[117],"than":[118,244],"19":[119],"million":[120],"configurations":[123,147,155],"train":[127],"evaluate":[129,215],"these":[130],"previously":[133],"unseen":[134],"Furthermore,":[140],"are":[143],"jointly":[145],"both":[149],"3":[150],"4":[152],"whose":[156],"shape":[157],"varies":[158],"along":[159,224],"1-parameter":[161],"family":[162],"increasing":[164],"elongation.":[165],"In":[166,194],"experiments,":[167],"study":[169],"how":[170,185],"networks'":[172],"performance":[173],"depends":[174],"size":[177],"training":[180,192],"dataset,":[181],"as":[182,184],"well":[183],"efficiently":[187],"deal":[188],"with":[189],"unevenly":[190],"distributed":[191],"data.":[193],"further":[195],"analysis,":[196],"show":[198,229],"evaluation":[201,223,231],"approximately":[204],"connected":[206],"regions":[207],"successful":[209],"placements":[212],"continuity":[217],"score":[222],"trajectories.":[227],"Experiments":[228],"given":[234],"GeForce":[238],"GTX":[239],"1080":[240],"GPU":[241],"takes":[242],"less":[243],"6":[245],"ms.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}