{"id":"https://openalex.org/W4408399423","doi":"https://doi.org/10.1109/tim.2025.3550952","title":"Improving Grasp Pose Detection by Implicitly Utilizing Geometric Information and Spatial Relations of Objects in Clutter","display_name":"Improving Grasp Pose Detection by Implicitly Utilizing Geometric Information and Spatial Relations of Objects in Clutter","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408399423","doi":"https://doi.org/10.1109/tim.2025.3550952"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2025.3550952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3550952","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5009524384","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0003-1101-3221"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0003-1101-3221","affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038287028","display_name":"Yunzhou Zhang","orcid":"https://orcid.org/0000-0003-0610-3732"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunzhou Zhang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0003-0610-3732","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076895776","display_name":"Shangdong Zhu","orcid":"https://orcid.org/0000-0003-4701-2028"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangdong Zhu","raw_affiliation_strings":["School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4701-2028","affiliations":[{"raw_affiliation_string":"School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111539765","display_name":"He Cao","orcid":"https://orcid.org/0009-0006-3486-2620"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Cao","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0006-3486-2620","affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075998258","display_name":"Le Zhou","orcid":"https://orcid.org/0009-0005-7718-2791"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Zhou","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0005-7718-2791","affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018818552","display_name":"Yixiu Liu","orcid":"https://orcid.org/0000-0002-4630-3774"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixiu Liu","raw_affiliation_strings":["School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4630-3774","affiliations":[{"raw_affiliation_string":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.4982,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.9178843,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9980000257492065,"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":0.9980000257492065,"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":0.9932000041007996,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9829000234603882,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.8894716501235962},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.8114246129989624},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6556360125541687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6552116870880127},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6316178441047668},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4518340528011322},{"id":"https://openalex.org/keywords/spatial-relation","display_name":"Spatial relation","score":0.44380733370780945},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3257821500301361},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.13956257700920105}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8894716501235962},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.8114246129989624},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6556360125541687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6552116870880127},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6316178441047668},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4518340528011322},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.44380733370780945},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3257821500301361},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.13956257700920105},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2025.3550952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3550952","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2007767059","display_name":null,"funder_award_id":"61471110","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3154569693","display_name":null,"funder_award_id":"WD2C20205500306","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4285396571","display_name":null,"funder_award_id":"61973066","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1820657498","https://openalex.org/W2031367292","https://openalex.org/W2036637075","https://openalex.org/W2085949256","https://openalex.org/W2140173255","https://openalex.org/W2344109021","https://openalex.org/W2600030077","https://openalex.org/W2824754393","https://openalex.org/W2889969363","https://openalex.org/W2962737955","https://openalex.org/W2963033241","https://openalex.org/W2963125977","https://openalex.org/W2986303149","https://openalex.org/W3034239841","https://openalex.org/W3035198432","https://openalex.org/W3090814639","https://openalex.org/W3111535274","https://openalex.org/W3187686865","https://openalex.org/W3203218344","https://openalex.org/W3204876017","https://openalex.org/W3205933337","https://openalex.org/W4210954285","https://openalex.org/W4221153162","https://openalex.org/W4285102142","https://openalex.org/W4285102491","https://openalex.org/W4311415873","https://openalex.org/W4313037736","https://openalex.org/W4385245566","https://openalex.org/W4389665589","https://openalex.org/W4399666511","https://openalex.org/W4402562091","https://openalex.org/W4402593284","https://openalex.org/W6636808768","https://openalex.org/W6691905554","https://openalex.org/W6735377749","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6769823609"],"related_works":["https://openalex.org/W2163296013","https://openalex.org/W2743859443","https://openalex.org/W2326995835","https://openalex.org/W165915117","https://openalex.org/W2059402478","https://openalex.org/W2123347777","https://openalex.org/W4387804363","https://openalex.org/W2019547100","https://openalex.org/W2477150073","https://openalex.org/W2515493494"],"abstract_inverted_index":{"6":[0],"degrees":[1],"of":[2,35,103,162],"freedom":[3],"(6-DoF)":[4],"grasp":[5,60,77,83,145,153,166,174,187],"pose":[6],"detection":[7,23],"in":[8,16,37,40,65,233,241],"clutter":[9],"is":[10],"an":[11,52,95],"essential":[12],"but":[13],"challenging":[14],"task":[15],"the":[17,29,71,76,100,111,119,128,182,197,239],"vision":[18],"measurement.":[19],"However,":[20],"most":[21,72],"current":[22],"methods":[24],"often":[25],"fail":[26],"to":[27,56,105,139,180],"consider":[28],"geometric":[30,101],"information":[31,102],"and":[32,44,79,89,113,133,164,189,214,235],"partial":[33],"occlusions":[34],"objects":[36,104,132,195],"clutter,":[38],"resulting":[39],"inaccurate":[41],"robotic":[42],"grasping":[43,54,205,232],"potential":[45],"collisions.":[46],"In":[47],"this":[48],"work,":[49],"we":[50,93,125,176],"propose":[51],"end-to-end":[53],"system":[55,68,206],"directly":[57,140],"generate":[58,159],"6-DoF":[59],"poses":[61,167],"from":[62,110,147],"point":[63],"clouds":[64],"clutter.":[66,242],"Our":[67],"first":[69],"selects":[70],"feasible":[73],"positions":[74],"as":[75,86,144],"centers,":[78,154],"then":[80,190],"determines":[81],"their":[82],"parameters,":[84,175],"such":[85],"approaching":[87],"vectors":[88],"in-plane":[90],"rotations.":[91],"Specifically,":[92],"design":[94],"optimality":[96],"criterion":[97],"based":[98],"on":[99,127,151,218],"extract":[106],"rich":[107],"object":[108],"features":[109],"scene":[112],"identify":[114],"high-graspablity":[115,148],"areas.":[116,149],"To":[117,171],"alleviate":[118],"collision":[120,137],"problem":[121],"caused":[122],"by":[123,209],"occlusions,":[124],"focus":[126],"spatial":[129],"relations":[130,193],"among":[131,194],"explicitly":[134],"train":[135],"a":[136,210,220,227],"predictor":[138],"select":[141],"collision-free":[142,163],"points":[143],"centers":[146],"Based":[150],"these":[152],"our":[155,204,224],"model":[156],"can":[157],"easily":[158],"diverse":[160],"sets":[161],"robust":[165],"for":[168,231],"successful":[169],"grasping.":[170],"efficiently":[172],"determine":[173],"exploit":[177],"neighbor":[178],"search":[179],"capture":[181],"local":[183],"context":[184],"around":[185],"each":[186],"center":[188],"implicitly":[191],"learn":[192],"using":[196],"self-attention":[198],"mechanism.":[199],"Compared":[200],"with":[201],"previous":[202],"methods,":[203],"improves":[207],"performance":[208],"large":[211],"margin":[212],"(>10%),":[213],"achieves":[215],"state-of-the-art":[216],"results":[217],"GraspNet-1Billion,":[219],"large-scale":[221],"dataset.":[222],"Besides,":[223],"method":[225],"has":[226],"high":[228],"success":[229],"rate":[230],"simulation":[234],"real-world":[236],"experiments,":[237],"verifying":[238],"validity":[240]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-18T10:00:31.954636","created_date":"2025-10-10T00:00:00"}