{"id":"https://openalex.org/W3003757902","doi":"https://doi.org/10.1109/iros40897.2019.8968093","title":"Detecting layered structures of partially occluded objects for bin picking","display_name":"Detecting layered structures of partially occluded objects for bin picking","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3003757902","doi":"https://doi.org/10.1109/iros40897.2019.8968093","mag":"3003757902"},"language":"en","primary_location":{"id":"doi:10.1109/iros40897.2019.8968093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8968093","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5113584777","display_name":"Yusuke Inagaki","orcid":null},"institutions":[{"id":"https://openalex.org/I184937672","display_name":"Chubu University","ror":"https://ror.org/02sps0775","country_code":"JP","type":"education","lineage":["https://openalex.org/I184937672"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusuke Inagaki","raw_affiliation_strings":["Chubu Univ,Dept. of Robotics Science and Technology, Grad,Aichi,JP","Dept. of Robotics Science and Technology, Grad, Chubu Univ, Aichi, JP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chubu Univ,Dept. of Robotics Science and Technology, Grad,Aichi,JP","institution_ids":["https://openalex.org/I184937672"]},{"raw_affiliation_string":"Dept. of Robotics Science and Technology, Grad, Chubu Univ, Aichi, JP","institution_ids":["https://openalex.org/I184937672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072874208","display_name":"Ryosuke Araki","orcid":"https://orcid.org/0000-0001-5935-6587"},"institutions":[{"id":"https://openalex.org/I184937672","display_name":"Chubu University","ror":"https://ror.org/02sps0775","country_code":"JP","type":"education","lineage":["https://openalex.org/I184937672"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryosuke Araki","raw_affiliation_strings":["Chubu Univ,Dept. of Computer Science, Grad,Aichi,JP","Dept. of Computer Science, Grad, Chubu Univ, Aichi, JP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chubu Univ,Dept. of Computer Science, Grad,Aichi,JP","institution_ids":["https://openalex.org/I184937672"]},{"raw_affiliation_string":"Dept. of Computer Science, Grad, Chubu Univ, Aichi, JP","institution_ids":["https://openalex.org/I184937672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062009349","display_name":"Takayoshi Yamashita","orcid":"https://orcid.org/0000-0003-2631-9856"},"institutions":[{"id":"https://openalex.org/I184937672","display_name":"Chubu University","ror":"https://ror.org/02sps0775","country_code":"JP","type":"education","lineage":["https://openalex.org/I184937672"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayoshi Yamashita","raw_affiliation_strings":["Chubu Univ,Faculty of Computer Science,Aichi,JP","Faculty of Computer Science, Chubu Univ, Aichi, JP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chubu Univ,Faculty of Computer Science,Aichi,JP","institution_ids":["https://openalex.org/I184937672"]},{"raw_affiliation_string":"Faculty of Computer Science, Chubu Univ, Aichi, JP","institution_ids":["https://openalex.org/I184937672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011810133","display_name":"Hironobu Fujiyoshi","orcid":"https://orcid.org/0000-0001-7391-4725"},"institutions":[{"id":"https://openalex.org/I184937672","display_name":"Chubu University","ror":"https://ror.org/02sps0775","country_code":"JP","type":"education","lineage":["https://openalex.org/I184937672"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hironobu Fujiyoshi","raw_affiliation_strings":["Chubu Univ,Faculty of Robotics Science and Technology,Aichi,JP","Faculty of Robotics Science and Technology, Chubu Univ, Aichi, JP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chubu Univ,Faculty of Robotics Science and Technology,Aichi,JP","institution_ids":["https://openalex.org/I184937672"]},{"raw_affiliation_string":"Faculty of Robotics Science and Technology, Chubu Univ, Aichi, JP","institution_ids":["https://openalex.org/I184937672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I184937672"],"apc_list":null,"apc_paid":null,"fwci":4.826,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.96700737,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5786","last_page":"5791"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9988999962806702,"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":0.9988999962806702,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.8083330392837524},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7726385593414307},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6563369631767273},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6116905212402344},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5400806665420532},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5381238460540771},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5189504623413086},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.49265724420547485},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4837084412574768},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4665776193141937},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.45288988947868347},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.44123703241348267},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.42829880118370056},{"id":"https://openalex.org/keywords/bin","display_name":"Bin","score":0.4228178858757019},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23300325870513916}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8083330392837524},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7726385593414307},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6563369631767273},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6116905212402344},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5400806665420532},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5381238460540771},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5189504623413086},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.49265724420547485},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4837084412574768},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4665776193141937},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.45288988947868347},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.44123703241348267},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.42829880118370056},{"id":"https://openalex.org/C156273044","wikidata":"https://www.wikidata.org/wiki/Q4913766","display_name":"Bin","level":2,"score":0.4228178858757019},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23300325870513916},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros40897.2019.8968093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8968093","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1910657905","https://openalex.org/W2037227137","https://openalex.org/W2076363786","https://openalex.org/W2086572812","https://openalex.org/W2295343990","https://openalex.org/W2962746398","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963881378","https://openalex.org/W3106250896"],"related_works":["https://openalex.org/W4287226069","https://openalex.org/W1967061043","https://openalex.org/W2369744843","https://openalex.org/W2383464976","https://openalex.org/W2019566805","https://openalex.org/W4213013926","https://openalex.org/W2756241593","https://openalex.org/W1987144139","https://openalex.org/W2801801420","https://openalex.org/W4312364477"],"abstract_inverted_index":{"When":[0],"robots":[1],"engage":[2],"in":[3,11],"bin":[4,84],"picking":[5,38,85],"of":[6,30,58,65,80,86,126,135,159],"multiple":[7,87],"objects,":[8],"a":[9,49,130,148],"failure":[10],"grasping":[12],"partially":[13],"occluded":[14,81,117,142],"objects":[15,20,31,59,128,160],"may":[16,21],"occur":[17],"because":[18],"other":[19],"overlap":[22],"the":[23,27,37,56,62,123,136,169],"desired":[24],"ones.":[25],"Therefore,":[26],"layered":[28,63,124,157],"structure":[29,125],"needs":[32,40],"to":[33,41],"be":[34,42,145,162],"detected,":[35],"and":[36,78,103,116,155],"order":[39],"established.":[43],"In":[44,67],"this":[45,68],"paper,":[46],"we":[47],"propose":[48],"new":[50],"dataset":[51,139,165],"that":[52,141,156],"evaluates":[53],"not":[54],"only":[55],"area":[57,118],"but":[60],"also":[61],"structures":[64,158],"objects.":[66,88],"dataset,":[69,90],"three":[70],"tasks":[71],"are":[72],"targeted:":[73],"object":[74],"detection,":[75],"semantic":[76,113],"segmentation,":[77],"segmentation":[79,114],"areas":[82,143],"for":[83],"The":[89],"called":[91],"\u201cthe":[92],"Amazon":[93],"Robotics":[94],"Challenge":[95],"(ARC)":[96],"Multi-task":[97],"Dataset\u201d":[98],"contains":[99],"1,500":[100],"RGB":[101],"images":[102],"depth":[104],"images,":[105],"including":[106],"all":[107],"scenes":[108],"containing":[109],"bounding":[110],"box":[111],"labels,":[112,115],"labels.":[119],"This":[120],"enables":[121],"representing":[122],"overlapped":[127],"with":[129],"tree":[131],"structure.":[132],"A":[133],"benchmark":[134],"ARC":[137],"multi-task":[138],"demonstrated":[140],"could":[144,161],"segmented":[146],"using":[147],"Mask":[149],"regional":[150],"convolutional":[151],"neural":[152],"network":[153],"(R-CNN)":[154],"predicted.":[163],"Our":[164],"is":[166],"available":[167],"at":[168],"following":[170],"URL:http://mprg.jp/research/arc_dataset_2017_e.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}