{"id":"https://openalex.org/W4383066501","doi":"https://doi.org/10.1109/icra48891.2023.10160405","title":"Learning Food Picking without Food: Fracture Anticipation by Breaking Reusable Fragile Objects","display_name":"Learning Food Picking without Food: Fracture Anticipation by Breaking Reusable Fragile Objects","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383066501","doi":"https://doi.org/10.1109/icra48891.2023.10160405"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160405","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/A5092393099","display_name":"Rinto Yagawa","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rinto Yagawa","raw_affiliation_strings":["Keio University,Yokohama,Japan,223-8522"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University,Yokohama,Japan,223-8522","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032745605","display_name":"Reina Ishikawa","orcid":"https://orcid.org/0000-0003-4792-6380"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Reina Ishikawa","raw_affiliation_strings":["Keio University,Yokohama,Japan,223-8522"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University,Yokohama,Japan,223-8522","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034718334","display_name":"Masashi Hamaya","orcid":"https://orcid.org/0000-0003-4189-8219"},"institutions":[{"id":"https://openalex.org/I146230289","display_name":"Omron (Japan)","ror":"https://ror.org/00q0w1h45","country_code":"JP","type":"company","lineage":["https://openalex.org/I146230289"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masashi Hamaya","raw_affiliation_strings":["OMRON SINIC X Corporation,Tokyo,Japan,113-0033"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OMRON SINIC X Corporation,Tokyo,Japan,113-0033","institution_ids":["https://openalex.org/I146230289"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045607922","display_name":"Kazutoshi Tanaka","orcid":"https://orcid.org/0000-0003-0880-9333"},"institutions":[{"id":"https://openalex.org/I146230289","display_name":"Omron (Japan)","ror":"https://ror.org/00q0w1h45","country_code":"JP","type":"company","lineage":["https://openalex.org/I146230289"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazutoshi Tanaka","raw_affiliation_strings":["OMRON SINIC X Corporation,Tokyo,Japan,113-0033"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OMRON SINIC X Corporation,Tokyo,Japan,113-0033","institution_ids":["https://openalex.org/I146230289"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038408644","display_name":"Atsushi Hashimoto","orcid":"https://orcid.org/0000-0002-0799-4269"},"institutions":[{"id":"https://openalex.org/I146230289","display_name":"Omron (Japan)","ror":"https://ror.org/00q0w1h45","country_code":"JP","type":"company","lineage":["https://openalex.org/I146230289"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Hashimoto","raw_affiliation_strings":["OMRON SINIC X Corporation,Tokyo,Japan,113-0033"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OMRON SINIC X Corporation,Tokyo,Japan,113-0033","institution_ids":["https://openalex.org/I146230289"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005819073","display_name":"Hideo Sait\u00f4","orcid":"https://orcid.org/0000-0002-2421-9862"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideo Saito","raw_affiliation_strings":["Keio University,Yokohama,Japan,223-8522"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University,Yokohama,Japan,223-8522","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3442,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5672909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"917","last_page":"923"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9966999888420105,"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6638126373291016},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6485750079154968},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6397479176521301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5820296406745911},{"id":"https://openalex.org/keywords/anticipation","display_name":"Anticipation (artificial intelligence)","score":0.5365512371063232}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6638126373291016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6485750079154968},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6397479176521301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5820296406745911},{"id":"https://openalex.org/C176777502","wikidata":"https://www.wikidata.org/wiki/Q4774623","display_name":"Anticipation (artificial intelligence)","level":2,"score":0.5365512371063232}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160405","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":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2057299504","https://openalex.org/W2064675550","https://openalex.org/W2155747683","https://openalex.org/W2281096776","https://openalex.org/W2604763608","https://openalex.org/W2623551786","https://openalex.org/W2781729746","https://openalex.org/W2784648116","https://openalex.org/W2804941773","https://openalex.org/W2911178129","https://openalex.org/W2911379339","https://openalex.org/W2944056254","https://openalex.org/W2955383310","https://openalex.org/W2963043696","https://openalex.org/W2967509406","https://openalex.org/W3020718655","https://openalex.org/W3023048440","https://openalex.org/W3045714531","https://openalex.org/W3091451982","https://openalex.org/W3092053846","https://openalex.org/W3098436915","https://openalex.org/W3125943082","https://openalex.org/W3127031155","https://openalex.org/W3130984490","https://openalex.org/W3133406196","https://openalex.org/W3134395475","https://openalex.org/W3154934604","https://openalex.org/W3165911584","https://openalex.org/W3206827162","https://openalex.org/W4205684198","https://openalex.org/W4205996330","https://openalex.org/W4213417100","https://openalex.org/W4221143455","https://openalex.org/W4225492355","https://openalex.org/W4287632120","https://openalex.org/W4296079286","https://openalex.org/W6736057607","https://openalex.org/W6762076930","https://openalex.org/W6785022050","https://openalex.org/W6790066379"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2150761772","https://openalex.org/W4213201576","https://openalex.org/W2765459612","https://openalex.org/W1525751611","https://openalex.org/W4285549518","https://openalex.org/W1579870145","https://openalex.org/W2913976737","https://openalex.org/W2381419481","https://openalex.org/W2114148396"],"abstract_inverted_index":{"Food":[0],"picking":[1,109],"is":[2,90,174],"trivial":[3],"for":[4,8,52,63,80,176],"humans":[5],"but":[6],"not":[7,19],"robots,":[9],"as":[10],"foods":[11,105],"are":[12],"fragile.":[13],"Presetting":[14],"foods'":[15],"physical":[16],"properties":[17],"does":[18],"help":[20],"robots":[21,62],"much":[22],"due":[23],"to":[24,55,67,91],"the":[25,47,50,93,108,135,147,164,177],"objects'":[26,169],"inter-":[27],"and":[28,60,130,142,158,172],"intra-category":[29,58],"diversity.":[30],"A":[31],"recent":[32],"study":[33,75],"proved":[34],"that":[35,163],"learning-based":[36],"fracture":[37,138],"anticipation":[38],"with":[39,57,112,123,149],"tactile":[40],"sensors":[41],"could":[42],"overcome":[43],"this":[44],"problem;":[45],"however,":[46],"method":[48],"trains":[49],"model":[51,122,148],"each":[53,64],"food":[54,65,72,152],"deal":[56],"differences,":[59],"tuning":[61],"leads":[66],"an":[68],"undesirable":[69],"amount":[70],"of":[71,96,102,167],"consumption.":[73],"This":[74],"proposes":[76],"a":[77,121],"novel":[78],"framework":[79],"learning":[81],"food-picking":[82,178],"tasks":[83],"without":[84],"consuming":[85,103],"foods.":[86],"The":[87,160],"key":[88],"idea":[89],"leverage":[92],"object-breaking":[94],"experiences":[95,171],"several":[97],"reusable":[98,124,168],"fragile":[99],"objects":[100,125,153],"instead":[101],"real":[104,151],"while":[106],"making":[107],"ability":[110],"object-invariant":[111],"domain":[113],"generalization":[114],"(DG).":[115],"In":[116],"real-robot":[117],"experiments,":[118],"we":[119],"trained":[120],"(toy":[126],"blocks,":[127],"ping-pong":[128],"balls,":[129],"jellies),":[131],"selected":[132],"based":[133],"on":[134],"three":[136],"common":[137],"types":[139],"(crack,":[140],"rupture,":[141],"crush).":[143],"We":[144],"then":[145],"tested":[146],"four":[150],"(tofu,":[154],"bananas,":[155],"potato":[156],"chips,":[157],"tomatoes).":[159],"results":[161],"showed":[162],"proposed":[165],"combination":[166],"breaking":[170],"DG":[173],"effective":[175],"task.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
