{"id":"https://openalex.org/W7128425625","doi":"https://doi.org/10.1109/tii.2025.3643916","title":"MSP-Grasp: Multiscale Perceptual Framework for 6-DoF Grasping in Cluttered Environments","display_name":"MSP-Grasp: Multiscale Perceptual Framework for 6-DoF Grasping in Cluttered Environments","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128425625","doi":"https://doi.org/10.1109/tii.2025.3643916"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2025.3643916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3643916","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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":null,"display_name":"Zhan Liu","orcid":"https://orcid.org/0000-0002-4345-2643"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhan Liu","raw_affiliation_strings":["Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4345-2643","affiliations":[{"raw_affiliation_string":"Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115767836","display_name":"Ziwei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ziwei Wang","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, and the Perception and Embodied Intelligence (PINE) Lab 50 Nanyang Avenue, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-9225-8495","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, and the Perception and Embodied Intelligence (PINE) Lab 50 Nanyang Avenue, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125445721","display_name":"Lei Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4279-3892","affiliations":[{"raw_affiliation_string":"Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jie Zhou","orcid":"https://orcid.org/0000-0001-7701-234X"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhou","raw_affiliation_strings":["Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7701-234X","affiliations":[{"raw_affiliation_string":"Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103740674","display_name":"Jiwen Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwen Lu","raw_affiliation_strings":["Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6121-5529","affiliations":[{"raw_affiliation_string":"Department of Automation and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13364311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"4","first_page":"3447","last_page":"3458"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.973800003528595,"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":0.973800003528595,"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/T10982","display_name":"Motor Control and Adaptation","score":0.006899999920278788,"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"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.003800000064074993,"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/grasp","display_name":"GRASP","score":0.8944000005722046},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6676999926567078},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.6175000071525574},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.5993000268936157},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5764999985694885},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47540000081062317},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.44609999656677246},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4406999945640564}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.8944000005722046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204999923706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6966000199317932},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6676999926567078},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.6175000071525574},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.5993000268936157},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5764999985694885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.541100025177002},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47540000081062317},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.3206000030040741},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.2971999943256378},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.29339998960494995},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tii.2025.3643916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3643916","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/212167","is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/212167","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2438210826","display_name":null,"funder_award_id":"62321005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5196092873","display_name":null,"funder_award_id":"L247009","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G588708310","display_name":null,"funder_award_id":"62306031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6358389640","display_name":null,"funder_award_id":"6212560","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"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"grasping":[1,47,71,85],"in":[2,12,48],"cluttered":[3,50],"environments":[4,128],"represents":[5],"one":[6],"of":[7,17,31,69,121],"the":[8,29,67,119],"most":[9],"challenging":[10],"problems":[11],"robotic":[13,46],"manipulation.":[14],"The":[15],"presence":[16],"occlusions":[18],"and":[19,26,76,117,129,147],"densely":[20],"packed":[21],"objects":[22],"significantly":[23],"complicates":[24],"perception":[25,58],"substantially":[27,137],"increases":[28],"risk":[30],"collisions.":[32],"To":[33],"address":[34],"these":[35],"challenges,":[36],"we":[37],"present":[38],"a":[39,55,61,88,105],"novel":[40],"multiscale":[41,56],"perception-based":[42],"framework":[43],"for":[44],"robust":[45],"dense,":[49],"environments.":[51],"Our":[52],"methodology":[53],"adopts":[54],"progressive":[57],"architecture:":[59],"First,":[60],"global":[62],"context":[63],"awareness":[64],"module":[65,92,109],"analyzes":[66],"distribution":[68],"viable":[70],"opportunities,":[72],"assesses":[73],"collision":[74,90,98],"risks,":[75],"evaluates":[77],"spatial":[78,102],"optimization":[79],"potential":[80],"to":[81,141],"systematically":[82],"identify":[83],"optimal":[84],"regions.":[86],"Second,":[87],"regional":[89],"prediction":[91],"provides":[93],"intermediate-scale":[94],"analysis,":[95],"effectively":[96],"reducing":[97],"incidents":[99],"through":[100],"enhanced":[101],"awareness.":[103],"Finally,":[104],"local":[106],"grasp":[107,111,122],"evaluation":[108],"refines":[110],"selection":[112],"by":[113],"optimizing":[114],"stability":[115],"metrics":[116],"predicting":[118],"probability":[120],"success.":[123],"Comprehensive":[124],"experiments":[125],"across":[126],"simulated":[127],"real-world":[130],"scenarios":[131],"demonstrate":[132],"that":[133],"our":[134],"approach":[135],"achieves":[136],"superior":[138],"performance":[139],"compared":[140],"existing":[142],"baselines,":[143],"confirming":[144],"its":[145],"effectiveness":[146],"applicability.":[148]},"counts_by_year":[],"updated_date":"2026-04-07T06:01:17.266235","created_date":"2026-02-10T00:00:00"}
