{"id":"https://openalex.org/W4383097520","doi":"https://doi.org/10.1109/icra48891.2023.10160986","title":"DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets","display_name":"DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383097520","doi":"https://doi.org/10.1109/icra48891.2023.10160986"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","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/A5064606654","display_name":"Isabella Huang","orcid":"https://orcid.org/0000-0002-4601-2782"},"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"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Isabella Huang","raw_affiliation_strings":["University of California,Department of Electrical Engineering and Computer Sciences,Berkeley,USA","Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Electrical Engineering and Computer Sciences,Berkeley,USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043295239","display_name":"Yashraj Narang","orcid":"https://orcid.org/0000-0001-5445-3759"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yashraj Narang","raw_affiliation_strings":["NVIDIA Corporation,Seattle,USA","NVIDIA Corporation, Seattle, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA Corporation,Seattle,USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]},{"raw_affiliation_string":"NVIDIA Corporation, Seattle, USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055278920","display_name":"R\u016f\u017eena Bajcsy","orcid":"https://orcid.org/0000-0001-6492-8498"},"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"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruzena Bajcsy","raw_affiliation_strings":["University of California,Department of Electrical Engineering and Computer Sciences,Berkeley,USA","Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Electrical Engineering and Computer Sciences,Berkeley,USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062619542","display_name":"F\u00e1bio Ramos","orcid":"https://orcid.org/0000-0002-2996-2188"},"institutions":[{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]},{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]},{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU","US"],"is_corresponding":false,"raw_author_name":"Fabio Ramos","raw_affiliation_strings":["NVIDIA Corporation,Seattle,USA","School of Computer Science, University of Sydney, Sydney, Australia","NVIDIA Corporation, Seattle, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA Corporation,Seattle,USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]},{"raw_affiliation_string":"School of Computer Science, University of Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]},{"raw_affiliation_string":"NVIDIA Corporation, Seattle, USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000432183","display_name":"Tucker Hermans","orcid":"https://orcid.org/0000-0003-2496-2768"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]},{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tucker Hermans","raw_affiliation_strings":["NVIDIA Corporation,Seattle,USA","NVIDIA Corporation, Seattle, USA","School of Computing, University of Utah, Salt Lake City, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA Corporation,Seattle,USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]},{"raw_affiliation_string":"NVIDIA Corporation, Seattle, USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]},{"raw_affiliation_string":"School of Computing, University of Utah, Salt Lake City, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108257764","display_name":"Dieter Fox","orcid":"https://orcid.org/0009-0009-4694-9127"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]},{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dieter Fox","raw_affiliation_strings":["NVIDIA Corporation,Seattle,USA","Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, USA","NVIDIA Corporation, Seattle, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA Corporation,Seattle,USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]},{"raw_affiliation_string":"Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, USA","institution_ids":["https://openalex.org/I201448701","https://openalex.org/I58610484"]},{"raw_affiliation_string":"NVIDIA Corporation, Seattle, USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I58610484"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5064606654"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":1.1288,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77520419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5894","last_page":"5901"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9180999994277954,"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/T10571","display_name":"Robotic Mechanisms and Dynamics","score":0.9017999768257141,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.957260251045227},{"id":"https://openalex.org/keywords/finite-element-method","display_name":"Finite element method","score":0.6972845196723938},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6850118637084961},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.637576162815094},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5636521577835083},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5030578970909119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49524012207984924},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4375643730163574},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4176483750343323},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3340132534503937},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29472577571868896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1463257074356079},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.12614646553993225},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.124614417552948}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.957260251045227},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.6972845196723938},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6850118637084961},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.637576162815094},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5636521577835083},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5030578970909119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49524012207984924},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4375643730163574},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4176483750343323},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3340132534503937},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29472577571868896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1463257074356079},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.12614646553993225},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.124614417552948},{"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":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W1505952289","https://openalex.org/W1564897360","https://openalex.org/W1762028192","https://openalex.org/W1995414376","https://openalex.org/W1999156278","https://openalex.org/W2005824379","https://openalex.org/W2075673359","https://openalex.org/W2106900371","https://openalex.org/W2109998105","https://openalex.org/W2155841413","https://openalex.org/W2511837229","https://openalex.org/W2600030077","https://openalex.org/W2805516822","https://openalex.org/W2808405904","https://openalex.org/W2895524695","https://openalex.org/W2899283552","https://openalex.org/W2901943374","https://openalex.org/W2910744956","https://openalex.org/W2922004937","https://openalex.org/W2959076435","https://openalex.org/W2962727772","https://openalex.org/W2963125977","https://openalex.org/W2968042644","https://openalex.org/W2986303149","https://openalex.org/W2995253198","https://openalex.org/W2996175471","https://openalex.org/W2996324165","https://openalex.org/W3007913393","https://openalex.org/W3014041360","https://openalex.org/W3048473624","https://openalex.org/W3089542352","https://openalex.org/W3090651099","https://openalex.org/W3091248659","https://openalex.org/W3105664040","https://openalex.org/W3109952375","https://openalex.org/W3119092717","https://openalex.org/W3122738733","https://openalex.org/W3127216876","https://openalex.org/W3142960102","https://openalex.org/W3159812989","https://openalex.org/W3163993681","https://openalex.org/W3164946289","https://openalex.org/W3173446233","https://openalex.org/W3174011998","https://openalex.org/W3194488868","https://openalex.org/W3207287914","https://openalex.org/W3207777114","https://openalex.org/W3212601792","https://openalex.org/W3213974477","https://openalex.org/W3214811308","https://openalex.org/W3216705422","https://openalex.org/W4210549532","https://openalex.org/W4224879709","https://openalex.org/W4225492355","https://openalex.org/W4229451778","https://openalex.org/W4281763194","https://openalex.org/W4287113927","https://openalex.org/W4287645102","https://openalex.org/W4301014524","https://openalex.org/W4301430473","https://openalex.org/W4302422232","https://openalex.org/W4312465063","https://openalex.org/W4365142055","https://openalex.org/W4380450805","https://openalex.org/W6638908295","https://openalex.org/W6725708968","https://openalex.org/W6751796012","https://openalex.org/W6755722174","https://openalex.org/W6762542935","https://openalex.org/W6769017845","https://openalex.org/W6771619427","https://openalex.org/W6783741718","https://openalex.org/W6784172082","https://openalex.org/W6790030675","https://openalex.org/W6793304456","https://openalex.org/W6794741268","https://openalex.org/W6796721163","https://openalex.org/W6800004206","https://openalex.org/W6803707382","https://openalex.org/W6809907836","https://openalex.org/W6810112079"],"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":{"Robotic":[0],"grasping":[1],"of":[2,29,79,83],"3D":[3,23,36,63,144,174],"deformable":[4,24],"objects":[5,25],"is":[6,72],"critical":[7],"for":[8,55],"real-world":[9,185,197],"applications":[10],"such":[11],"as":[12,75,135],"food":[13],"handling":[14],"and":[15,20,38,146,176,189],"robotic":[16],"surgery.":[17],"Unlike":[18],"rigid":[19],"articulated":[21],"objects,":[22],"have":[26],"infinite":[27],"degrees":[28],"freedom.":[30],"Fully":[31],"defining":[32],"their":[33],"state":[34],"requires":[35,59,77,94],"deformation":[37,147,177],"stress":[39,145,175],"fields,":[40],"which":[41],"are":[42,113],"exceptionally":[43],"difficult":[44],"to":[45,98,133,142,159,182],"analytically":[46],"compute":[47],"or":[48],"experimentally":[49],"measure.":[50],"Thus,":[51],"evaluating":[52],"grasp":[53,56,70,84,87,152,171,186],"candidates":[54],"planning":[57,71,88,187],"typically":[58,114],"accurate,":[60],"but":[61,93,112,166],"slow":[62],"finite":[64],"element":[65],"method":[66],"(FEM)":[67],"simulation.":[68],"Sampling-based":[69],"often":[73],"impractical,":[74],"it":[76],"evaluation":[78],"a":[80,95,126],"large":[81],"number":[82],"candidates.":[85,104],"Gradient-based":[86],"can":[89],"be":[90],"more":[91],"efficient,":[92],"differentiable":[96,137],"model":[97],"synthesize":[99],"optimal":[100],"grasps":[101],"from":[102],"initial":[103],"Differentiable":[105],"FEM":[106,164],"simulators":[107],"may":[108],"fill":[109],"this":[110,121],"role,":[111],"no":[115],"faster":[116,161],"than":[117,162],"standard":[118],"FEM.":[119],"In":[120],"work,":[122],"we":[123],"propose":[124],"learning":[125],"predictive":[127],"graph":[128],"neural":[129],"network":[130],"(GNN),":[131],"DefGraspNets,":[132],"act":[134],"our":[136],"model.":[138],"We":[139,179],"train":[140],"DefGraspNets":[141,154,181],"predict":[143],"fields":[148],"based":[149],"on":[150],"FEM-based":[151],"simulations.":[153],"not":[155],"only":[156],"runs":[157],"up":[158],"1500x":[160],"the":[163],"simulator,":[165],"also":[167],"enables":[168],"fast":[169],"gradient-based":[170],"optimization":[172],"over":[173],"metrics.":[178],"design":[180],"align":[183],"with":[184],"practices":[188],"demonstrate":[190],"generalization":[191],"across":[192],"multiple":[193],"test":[194],"sets,":[195],"including":[196],"experiments.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}