{"id":"https://openalex.org/W7166687493","doi":"https://doi.org/10.48550/arxiv.2606.29924","title":"DCGrasp: Distance-aware Controllable Grasp Generation","display_name":"DCGrasp: Distance-aware Controllable Grasp Generation","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166687493","doi":"https://doi.org/10.48550/arxiv.2606.29924"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.29924","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29924","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.29924","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067830872","display_name":"Hiroyasu Akada","orcid":"https://orcid.org/0000-0002-3204-6391"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akada, Hiroyasu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139655871","display_name":"Jes\u00fas P\u00e9rez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P\u00e9rez, Jes\u00fas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044027671","display_name":"Emre Aksan","orcid":"https://orcid.org/0000-0002-9836-9011"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aksan, Emre","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048464691","display_name":"Vasileios Choutas","orcid":"https://orcid.org/0009-0004-4375-3368"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choutas, Vasileios","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043162154","display_name":"Cristian Romero","orcid":"https://orcid.org/0000-0002-1180-4595"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Romero, Cristian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104090678","display_name":"A. Garc\u00eda-Garc\u00eda","orcid":"https://orcid.org/0000-0001-9561-4977"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garcia-Garcia, Alberto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080103406","display_name":"Vladislav Golyanik","orcid":"https://orcid.org/0000-0003-1630-2006"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Golyanik, Vladislav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020664641","display_name":"Christian Theobalt","orcid":"https://orcid.org/0000-0001-6104-6625"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Theobalt, Christian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5013075810","display_name":"Thabo Beeler","orcid":"https://orcid.org/0000-0002-8077-1205"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Beeler, Thabo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.8659999966621399,"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":0.8659999966621399,"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":0.049800001084804535,"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/T10789","display_name":"Interactive and Immersive Displays","score":0.0272000003606081,"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":0.9000999927520752},{"id":"https://openalex.org/keywords/controllability","display_name":"Controllability","score":0.7486000061035156},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5317999720573425},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5299999713897705},{"id":"https://openalex.org/keywords/grippers","display_name":"Grippers","score":0.4754999876022339},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.3944000005722046},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.36149999499320984},{"id":"https://openalex.org/keywords/observability","display_name":"Observability","score":0.3449999988079071}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9000999927520752},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.7486000061035156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.578499972820282},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5317999720573425},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5299999713897705},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.4754999876022339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41839998960494995},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3880000114440918},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.3449999988079071},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3131999969482422},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.30709999799728394},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C141898687","wikidata":"https://www.wikidata.org/wiki/Q1501997","display_name":"Hausdorff distance","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C73621898","wikidata":"https://www.wikidata.org/wiki/Q2940504","display_name":"Distance transform","level":3,"score":0.29679998755455017},{"id":"https://openalex.org/C71169176","wikidata":"https://www.wikidata.org/wiki/Q7512907","display_name":"Signed distance function","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C20894473","wikidata":"https://www.wikidata.org/wiki/Q1116105","display_name":"Object model","level":3,"score":0.2808000147342682},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26589998602867126},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2623000144958496}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.29924","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29924","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.29924","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29924","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.6893303990364075}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generating":[0],"3D":[1,174],"hand-object":[2,80,175],"interactions":[3],"is":[4],"essential":[5],"for":[6,169],"applications":[7],"in":[8,82,135],"robotics,":[9],"XR,":[10],"and":[11,18,90,130,156,159,166],"synthetic":[12],"data":[13],"generation,":[14],"where":[15],"flexible":[16,149],"controllability":[17],"strong":[19],"generalization":[20],"to":[21,66,88,153],"diverse":[22,154],"object":[23,69,89,155],"geometries":[24],"are":[25],"required.":[26],"However,":[27],"existing":[28],"methods":[29],"rarely":[30],"satisfy":[31],"these":[32],"requirements,":[33],"limiting":[34],"their":[35],"practical":[36],"applicability.":[37],"We":[38,115],"present":[39],"DCGrasp,":[40],"a":[41,49,59,100,105,110,164],"distance-aware":[42,73],"controllable":[43,95,173],"grasp":[44,51],"generation":[45],"system":[46],"built":[47],"on":[48,104],"novel":[50],"energy":[52],"term.":[53],"This":[54],"term":[55],"computes":[56],"Distance":[57,101,133],"Profile,":[58],"signed":[60],"distance":[61],"from":[62],"each":[63],"hand":[64,91,113,128,157],"vertex":[65],"the":[67,77,118,126,131,170],"nearest":[68],"point,":[70],"coupled":[71],"with":[72,109,148],"weighting,":[74],"effectively":[75],"capturing":[76],"semantically":[78],"similar":[79],"interaction":[81],"near-contact":[83,136],"regions":[84],"while":[85],"remaining":[86],"invariant":[87],"identity.":[92],"Given":[93],"various":[94],"signals,":[96],"DCGrasp":[97,142],"first":[98],"generates":[99],"Profile":[102,134],"based":[103],"Diffusion":[106],"Transformer,":[107],"together":[108],"corresponding":[111],"candidate":[112,119],"pose.":[114],"then":[116],"refine":[117],"pose":[120,129],"through":[121],"optimization,":[122],"enforcing":[123],"consistency":[124],"between":[125],"optimized":[127],"generated":[132],"regions.":[137],"Our":[138,161],"experiments":[139],"show":[140],"that":[141],"produces":[143],"high-quality,":[144],"physically":[145],"plausible":[146],"grasps":[147],"user":[150],"control,":[151],"generalizing":[152],"shapes":[158],"scales.":[160],"work":[162],"establishes":[163],"robust":[165],"versatile":[167],"pipeline":[168],"synthesis":[171],"of":[172],"interactions.":[176]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}