{"id":"https://openalex.org/W4405785549","doi":"https://doi.org/10.1109/iros58592.2024.10801600","title":"Gravity-aware Grasp Generation with Implicit Grasp Mode Selection for Underactuated Hands","display_name":"Gravity-aware Grasp Generation with Implicit Grasp Mode Selection for Underactuated Hands","publication_year":2024,"publication_date":"2024-10-14","ids":{"openalex":"https://openalex.org/W4405785549","doi":"https://doi.org/10.1109/iros58592.2024.10801600"},"language":"en","primary_location":{"id":"doi:10.1109/iros58592.2024.10801600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10801600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5034562879","display_name":"Tianyi Ko","orcid":"https://orcid.org/0000-0002-2576-9161"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tianyi Ko","raw_affiliation_strings":["Woven by Toyota, Inc.,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Woven by Toyota, Inc.,Tokyo,Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102963090","display_name":"Takuya Ikeda","orcid":"https://orcid.org/0000-0002-3312-5120"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takuya Ikeda","raw_affiliation_strings":["Woven by Toyota, Inc.,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Woven by Toyota, Inc.,Tokyo,Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044077121","display_name":"Thomas Stewart","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thomas Stewart","raw_affiliation_strings":["Woven by Toyota, Inc.,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Woven by Toyota, Inc.,Tokyo,Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039562009","display_name":"Robert Lee","orcid":"https://orcid.org/0000-0001-7535-3554"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robert Lee","raw_affiliation_strings":["Woven by Toyota, Inc.,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Woven by Toyota, Inc.,Tokyo,Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113446235","display_name":"Koichi Nishiwaki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koichi Nishiwaki","raw_affiliation_strings":["Woven by Toyota, Inc.,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Woven by Toyota, Inc.,Tokyo,Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5034562879"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6989,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73315015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2964","last_page":"2970"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9965999722480774,"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":0.9965999722480774,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10879","display_name":"Robotic Locomotion and Control","score":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.9463100433349609},{"id":"https://openalex.org/keywords/underactuation","display_name":"Underactuation","score":0.830742359161377},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6523949503898621},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5309137105941772},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.4964187741279602},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.34872114658355713},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.2694213390350342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2556348145008087},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.20904284715652466},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.0737130343914032}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9463100433349609},{"id":"https://openalex.org/C88337583","wikidata":"https://www.wikidata.org/wiki/Q7883433","display_name":"Underactuation","level":3,"score":0.830742359161377},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6523949503898621},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5309137105941772},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.4964187741279602},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.34872114658355713},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2694213390350342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2556348145008087},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.20904284715652466},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0737130343914032}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros58592.2024.10801600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10801600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1503925285","https://openalex.org/W1505952289","https://openalex.org/W1560270123","https://openalex.org/W1641694943","https://openalex.org/W1794703952","https://openalex.org/W2088043683","https://openalex.org/W2124505230","https://openalex.org/W2132476906","https://openalex.org/W2140294374","https://openalex.org/W2144573888","https://openalex.org/W2211217408","https://openalex.org/W2600030077","https://openalex.org/W2949924544","https://openalex.org/W2962737955","https://openalex.org/W2963033241","https://openalex.org/W3003653881","https://openalex.org/W3035198432","https://openalex.org/W3175388581","https://openalex.org/W3204876017","https://openalex.org/W3206683563","https://openalex.org/W3207187156","https://openalex.org/W3207888596","https://openalex.org/W4205745300","https://openalex.org/W4214570817","https://openalex.org/W4225759270","https://openalex.org/W4312254766","https://openalex.org/W4382366145","https://openalex.org/W4383109460","https://openalex.org/W6769823609","https://openalex.org/W6789211778"],"related_works":["https://openalex.org/W2163296013","https://openalex.org/W2743859443","https://openalex.org/W2326995835","https://openalex.org/W165915117","https://openalex.org/W2324418439","https://openalex.org/W2157487448","https://openalex.org/W2387707337","https://openalex.org/W4200004409","https://openalex.org/W2078568084","https://openalex.org/W1788667622"],"abstract_inverted_index":{"Learning-based":[0],"grasp":[1,19,59,90],"detectors":[2],"typically":[3],"assume":[4],"a":[5,26,58,89,111],"precision":[6,68],"grasp,":[7],"where":[8],"each":[9],"finger":[10],"only":[11],"has":[12,38],"one":[13],"contact":[14,40],"point,":[15],"and":[16,29,46,53,121],"estimate":[17],"the":[18,71,78,81,86,97,124,132],"probability.":[20],"In":[21],"this":[22],"work,":[23],"we":[24,74],"propose":[25,75],"data":[27,107],"generation":[28,108],"learning":[30],"pipeline":[31,109],"that":[32],"can":[33,91],"leverage":[34],"power":[35,63],"grasping,":[36],"which":[37],"more":[39],"points":[41],"with":[42,113],"an":[43,105],"enveloping":[44],"configuration":[45],"is":[47],"robust":[48],"against":[49,80],"both":[50,119],"positioning":[51],"error":[52],"force":[54],"disturbance.":[55],"To":[56],"train":[57,77],"detector":[60],"to":[61,76],"prioritize":[62],"grasping":[64,69],"while":[65],"still":[66],"keeping":[67],"as":[70],"secondary":[72],"choice,":[73],"network":[79],"magnitude":[82],"of":[83,100],"disturbance":[84],"in":[85,118,127],"gravity":[87],"direction":[88],"resist":[92],"(gravity-rejection":[93],"score)":[94],"rather":[95],"than":[96],"binary":[98],"classification":[99],"success.":[101],"We":[102],"also":[103],"provide":[104],"efficient":[106],"for":[110],"dataset":[112],"gravity-rejection":[114],"score":[115],"annotation.":[116],"Evaluation":[117],"simulation":[120],"real-robot":[122],"clarifies":[123],"significant":[125],"improvement":[126],"our":[128],"approach,":[129],"especially":[130],"when":[131],"objects":[133],"are":[134],"heavy.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}
