{"id":"https://openalex.org/W4413360447","doi":"https://doi.org/10.1109/mcte62870.2024.11118010","title":"Research on Robots Grasping Method for Disordered Mechanical Parts Based on 3D Vision","display_name":"Research on Robots Grasping Method for Disordered Mechanical Parts Based on 3D Vision","publication_year":2024,"publication_date":"2024-08-23","ids":{"openalex":"https://openalex.org/W4413360447","doi":"https://doi.org/10.1109/mcte62870.2024.11118010"},"language":"en","primary_location":{"id":"doi:10.1109/mcte62870.2024.11118010","doi":"https://doi.org/10.1109/mcte62870.2024.11118010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mcte62870.2024.11118010","pdf_url":null,"source":{"id":"https://openalex.org/S4363607940","display_name":"International Conference on Mechatronics and Computer Technology Engineering (MCTE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 7th International Conference on Mechatronics and Computer Technology Engineering (MCTE)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5100570846","display_name":"Chengjun Xiao","orcid":"https://orcid.org/0009-0009-0990-2055","observed_orcids":["https://orcid.org/0009-0009-0990-2055"]},"institutions":[{"id":"https://openalex.org/I4405281045","display_name":"Guangzhou Vocational College of Technology & Business","ror":"https://ror.org/03srptg92","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengjun Xiao","raw_affiliation_strings":["School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China","institution_ids":["https://openalex.org/I4405281045"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhouhai Lu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405281045","display_name":"Guangzhou Vocational College of Technology & Business","ror":"https://ror.org/03srptg92","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhouhai Lu","raw_affiliation_strings":["School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China","institution_ids":["https://openalex.org/I4405281045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010200298","display_name":"Jianfeng Lin","orcid":"https://orcid.org/0000-0001-5817-997X","observed_orcids":["https://orcid.org/0000-0001-5817-997X"]},"institutions":[{"id":"https://openalex.org/I4405281045","display_name":"Guangzhou Vocational College of Technology & Business","ror":"https://ror.org/03srptg92","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Lin","raw_affiliation_strings":["School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China","institution_ids":["https://openalex.org/I4405281045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004851163","display_name":"Hong Liang Wei","orcid":"https://orcid.org/0000-0002-2359-8522","observed_orcids":["https://orcid.org/0000-0002-2359-8522"]},"institutions":[{"id":"https://openalex.org/I4405281045","display_name":"Guangzhou Vocational College of Technology & Business","ror":"https://ror.org/03srptg92","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Wei","raw_affiliation_strings":["School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing, Guangzhou Vocational College of Technology & Business,Guangzhou,China","institution_ids":["https://openalex.org/I4405281045"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405281045"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"56","last_page":"59"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9994999766349792,"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":0.9994999766349792,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/robotic-grasping","display_name":"robotic grasping","score":0.8880000114440918},{"id":"https://openalex.org/keywords/3d-computer-vision","display_name":"3D vision","score":0.9750000238418579},{"id":"https://openalex.org/keywords/3d-point-clouds","display_name":"3D point clouds","score":0.9210000038146973},{"id":"https://openalex.org/keywords/object-pose-estimation","display_name":"object pose estimation","score":0.6740000247955322},{"id":"https://openalex.org/keywords/part-recognition","display_name":"part recognition","score":0.5059999823570251},{"id":"https://openalex.org/keywords/vision-based-robots","display_name":"vision-guided robots","score":0.5799999833106995},{"id":"https://openalex.org/keywords/industrial-automation","display_name":"industrial automation","score":0.4729999899864197}],"concepts":[{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6787687540054321},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6226486563682556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6105135679244995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5739269852638245},{"id":"https://openalex.org/C2983761899","wikidata":"https://www.wikidata.org/wiki/Q604674","display_name":"Robot vision","level":4,"score":0.5026693344116211},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.4421424865722656},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.26939600706100464}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mcte62870.2024.11118010","doi":"https://doi.org/10.1109/mcte62870.2024.11118010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mcte62870.2024.11118010","pdf_url":null,"source":{"id":"https://openalex.org/S4363607940","display_name":"International Conference on Mechatronics and Computer Technology Engineering (MCTE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 7th International Conference on Mechatronics and Computer Technology Engineering (MCTE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W3082043210","https://openalex.org/W4211037494","https://openalex.org/W4226357955","https://openalex.org/W4289821535","https://openalex.org/W4311519339","https://openalex.org/W4376105513","https://openalex.org/W4382203221"],"related_works":["https://openalex.org/W4392170014","https://openalex.org/W4402059017","https://openalex.org/W4386380755","https://openalex.org/W4397042324","https://openalex.org/W4307944536","https://openalex.org/W2013059900","https://openalex.org/W2973387153","https://openalex.org/W2120489233","https://openalex.org/W4414350479","https://openalex.org/W4402058466"],"abstract_inverted_index":{"The":[0,64,136],"increasing":[1],"pace":[2],"of":[3,35,40,77,102,149],"industrial":[4,17],"automation":[5],"is":[6,25,86,110,123],"driving":[7],"a":[8,26,38,53,67,90,133],"corresponding":[9],"rise":[10],"in":[11,19,132,147,154],"demand":[12,28],"for":[13,29,56],"intelligent":[14],"and":[15,47,96,100,128,152],"automated":[16],"robots":[18,31],"the":[20,72,78,81,98,106,114,121,130,141],"manufacturing":[21],"sector.":[22],"Concurrently,":[23],"there":[24],"growing":[27],"vision-based":[30],"that":[32,120,140],"are":[33],"capable":[34],"autonomously":[36],"performing":[37],"range":[39],"tasks,":[41],"including":[42],"object":[43],"recognition,":[44],"precise":[45],"grasping,":[46],"optimal":[48,115],"placement.":[49],"This":[50,84],"work":[51],"proposes":[52],"grasping":[54,150],"method":[55,65,143],"out-of-order":[57,156],"mechanical":[58],"parts":[59,79,131],"based":[60],"on":[61],"3D":[62,68,73],"vision.":[63],"employs":[66],"camera":[69],"to":[70,94,112,125],"obtain":[71],"point":[74],"cloud":[75],"data":[76,85],"within":[80],"operational":[82],"area.":[83],"then":[87],"processed":[88],"through":[89],"deep":[91],"learning":[92],"model":[93],"identify":[95],"locate":[97],"position":[99],"posture":[101],"each":[103],"part.":[104],"Subsequently,":[105],"gripping":[107,116],"planning":[108],"algorithm":[109],"employed":[111],"generate":[113],"path,":[117],"thereby":[118],"ensuring":[119],"robot":[122],"able":[124],"accurately":[126],"grasp":[127],"place":[129],"reasonable":[134],"manner.":[135],"experimental":[137],"analysis":[138],"demonstrates":[139],"proposed":[142],"exhibits":[144],"notable":[145],"advantages":[146],"terms":[148],"accuracy":[151],"efficiency":[153],"complex":[155],"scenes.":[157]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2025-10-10T00:00:00"}