{"id":"https://openalex.org/W2991687685","doi":"https://doi.org/10.1109/icra40945.2020.9197318","title":"6-DOF Grasping for Target-driven Object Manipulation in Clutter","display_name":"6-DOF Grasping for Target-driven Object Manipulation in Clutter","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W2991687685","doi":"https://doi.org/10.1109/icra40945.2020.9197318","mag":"2991687685"},"language":"en","primary_location":{"id":"doi:10.1109/icra40945.2020.9197318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9197318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.03628","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114179160","display_name":"Adithyavairavan Murali","orcid":null},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Adithyavairavan Murali","raw_affiliation_strings":["NVIDIA","nVidia"],"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]},{"raw_affiliation_string":"nVidia","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021728625","display_name":"Arsalan Mousavian","orcid":"https://orcid.org/0000-0001-9356-9455"},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Arsalan Mousavian","raw_affiliation_strings":["NVIDIA","nVidia"],"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]},{"raw_affiliation_string":"nVidia","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076300410","display_name":"Clemens Eppner","orcid":"https://orcid.org/0000-0002-5398-4037"},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Clemens Eppner","raw_affiliation_strings":["NVIDIA","nVidia"],"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]},{"raw_affiliation_string":"nVidia","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044926286","display_name":"Chris Paxton","orcid":null},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chris Paxton","raw_affiliation_strings":["NVIDIA","nVidia"],"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]},{"raw_affiliation_string":"nVidia","institution_ids":["https://openalex.org/I1304085615"]}]},{"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/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dieter Fox","raw_affiliation_strings":["NVIDIA","nVidia"],"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]},{"raw_affiliation_string":"nVidia","institution_ids":["https://openalex.org/I1304085615"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5114179160"],"corresponding_institution_ids":["https://openalex.org/I1304085615"],"apc_list":null,"apc_paid":null,"fwci":1.3351,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.7962624,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"6232","last_page":"6238"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9887999892234802,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9811000227928162,"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":0.8867179155349731},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7683895230293274},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7535713315010071},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7178333401679993},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7157516479492188},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.6990269422531128},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6138590574264526},{"id":"https://openalex.org/keywords/manipulator","display_name":"Manipulator (device)","score":0.5047985315322876},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.49253854155540466},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.49249085783958435},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4195302128791809},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3654133677482605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.11328551173210144},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1076638400554657},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.09610030055046082},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.08263584971427917}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.8867179155349731},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7683895230293274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7535713315010071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7178333401679993},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7157516479492188},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.6990269422531128},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6138590574264526},{"id":"https://openalex.org/C2781347998","wikidata":"https://www.wikidata.org/wiki/Q1587588","display_name":"Manipulator (device)","level":3,"score":0.5047985315322876},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.49253854155540466},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.49249085783958435},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4195302128791809},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3654133677482605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.11328551173210144},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1076638400554657},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.09610030055046082},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.08263584971427917},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icra40945.2020.9197318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9197318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1912.03628","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03628","pdf_url":"https://arxiv.org/pdf/1912.03628","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2991687685","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1912.03628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1912.03628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1912.03628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.03628","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03628","pdf_url":"https://arxiv.org/pdf/1912.03628","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2991687685.pdf","grobid_xml":"https://content.openalex.org/works/W2991687685.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W143499627","https://openalex.org/W1503925285","https://openalex.org/W1522963174","https://openalex.org/W1559022906","https://openalex.org/W1597612847","https://openalex.org/W1820657498","https://openalex.org/W1899217968","https://openalex.org/W1959608418","https://openalex.org/W1999156278","https://openalex.org/W2036637075","https://openalex.org/W2063189785","https://openalex.org/W2068127265","https://openalex.org/W2085949256","https://openalex.org/W2106270058","https://openalex.org/W2109447584","https://openalex.org/W2112961542","https://openalex.org/W2126496149","https://openalex.org/W2128082316","https://openalex.org/W2161047498","https://openalex.org/W2201912979","https://openalex.org/W2293467699","https://openalex.org/W2414685554","https://openalex.org/W2542011642","https://openalex.org/W2600030077","https://openalex.org/W2603737562","https://openalex.org/W2624503621","https://openalex.org/W2733441458","https://openalex.org/W2773721443","https://openalex.org/W2789805345","https://openalex.org/W2797250424","https://openalex.org/W2883654928","https://openalex.org/W2886380958","https://openalex.org/W2889969363","https://openalex.org/W2918333121","https://openalex.org/W2962722175","https://openalex.org/W2962737955","https://openalex.org/W2962746398","https://openalex.org/W2962976158","https://openalex.org/W2963117514","https://openalex.org/W2963121255","https://openalex.org/W2963484919","https://openalex.org/W2963654160","https://openalex.org/W2963894672","https://openalex.org/W2967068439","https://openalex.org/W2986303149","https://openalex.org/W3029330586","https://openalex.org/W4241088297","https://openalex.org/W6640963894","https://openalex.org/W6697071109","https://openalex.org/W6740972095","https://openalex.org/W6746713385","https://openalex.org/W6750987562","https://openalex.org/W6753243525","https://openalex.org/W6753766000","https://openalex.org/W6766284323"],"related_works":["https://openalex.org/W3090814639","https://openalex.org/W3150774829","https://openalex.org/W3186881096","https://openalex.org/W3123293341","https://openalex.org/W20791675","https://openalex.org/W3173002428","https://openalex.org/W3135494106","https://openalex.org/W2057493164","https://openalex.org/W2969014098","https://openalex.org/W2999821079","https://openalex.org/W3090139892","https://openalex.org/W3006627057","https://openalex.org/W3090458772","https://openalex.org/W2901198969","https://openalex.org/W3205933337","https://openalex.org/W3175388034","https://openalex.org/W3200879008","https://openalex.org/W3089949728","https://openalex.org/W3180079054","https://openalex.org/W2971942950"],"abstract_inverted_index":{"Grasping":[0],"in":[1,63,99],"cluttered":[2,65,88],"environments":[3],"is":[4,40],"a":[5,53,64,75,102],"fundamental":[6],"but":[7],"challenging":[8],"robotic":[9,104],"skill.":[10],"It":[11],"requires":[12],"both":[13],"reasoning":[14],"about":[15,117],"unseen":[16],"object":[17,62],"parts":[18],"and":[19,46,85,96],"potential":[20],"collisions":[21],"with":[22],"the":[23],"manipulator.":[24],"Most":[25],"existing":[26],"data-driven":[27],"approaches":[28,82],"avoid":[29],"this":[30],"problem":[31],"by":[32,83],"limiting":[33],"themselves":[34],"to":[35,121],"top-down":[36],"planar":[37],"grasps":[38,58],"which":[39],"insufficient":[41],"for":[42,59],"many":[43],"real-world":[44],"scenarios":[45],"greatly":[47],"limits":[48],"possible":[49],"grasps.":[50],"We":[51],"present":[52],"method":[54,73],"that":[55,124],"plans":[56],"6-DOF":[57],"any":[60],"desired":[61],"scene":[66],"from":[67],"partial":[68],"point":[69],"cloud":[70],"observations.":[71],"Our":[72],"achieves":[74],"grasp":[76,119],"success":[77],"of":[78],"80.3%,":[79],"outperforming":[80],"baseline":[81],"17.6%":[84],"clearing":[86],"9":[87],"table":[89],"scenes":[90],"(which":[91],"contain":[92],"23":[93],"unknown":[94],"objects":[95,123],"51":[97],"picks":[98],"total)":[100],"on":[101],"real":[103],"platform.":[105],"By":[106],"using":[107],"our":[108],"learned":[109],"collision":[110],"checking":[111],"module,":[112],"we":[113],"can":[114,131],"even":[115],"reason":[116],"effective":[118],"sequences":[120],"retrieve":[122],"are":[125],"not":[126],"immediately":[127],"accessible.":[128],"Supplementary":[129],"video":[130],"be":[132],"found":[133],"here.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}