{"id":"https://openalex.org/W7117236526","doi":"https://doi.org/10.1109/lra.2025.3645512","title":"Learning From Planned Data to Improve Robotic Pick-and-Place Planning Efficiency","display_name":"Learning From Planned Data to Improve Robotic Pick-and-Place Planning Efficiency","publication_year":2025,"publication_date":"2025-12-25","ids":{"openalex":"https://openalex.org/W7117236526","doi":"https://doi.org/10.1109/lra.2025.3645512"},"language":null,"primary_location":{"id":"doi:10.1109/lra.2025.3645512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3645512","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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 Robotics and Automation Letters","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/A5121255283","display_name":"Liang Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I11381156","display_name":"Osaka Gakuin University","ror":"https://ror.org/04a8t1e98","country_code":"JP","type":"education","lineage":["https://openalex.org/I11381156"]},{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Liang Qin","raw_affiliation_strings":["Graduate School of Engineering Science, The University of Osaka, Suita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, The University of Osaka, Suita, Japan","institution_ids":["https://openalex.org/I11381156","https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121296520","display_name":"Weiwei Wan","orcid":null},"institutions":[{"id":"https://openalex.org/I11381156","display_name":"Osaka Gakuin University","ror":"https://ror.org/04a8t1e98","country_code":"JP","type":"education","lineage":["https://openalex.org/I11381156"]},{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Weiwei Wan","raw_affiliation_strings":["Graduate School of Engineering Science, The University of Osaka, Suita, Japan"],"raw_orcid":"https://orcid.org/0000-0002-0058-2819","affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, The University of Osaka, Suita, Japan","institution_ids":["https://openalex.org/I11381156","https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121258942","display_name":"Jun Takahashi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125947","display_name":"Japan Research Institute","ror":"https://ror.org/02m5srn05","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210125947"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jun Takahashi","raw_affiliation_strings":["H.U. Group Research Institute G.K., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"H.U. Group Research Institute G.K., Tokyo, Japan","institution_ids":["https://openalex.org/I4210125947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121272253","display_name":"Ryo Negishi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125947","display_name":"Japan Research Institute","ror":"https://ror.org/02m5srn05","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210125947"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Negishi","raw_affiliation_strings":["H.U. Group Research Institute G.K., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"H.U. Group Research Institute G.K., Tokyo, Japan","institution_ids":["https://openalex.org/I4210125947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121262701","display_name":"Masaki Matsushita","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125947","display_name":"Japan Research Institute","ror":"https://ror.org/02m5srn05","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210125947"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaki Matsushita","raw_affiliation_strings":["H.U. Group Research Institute G.K., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"H.U. Group Research Institute G.K., Tokyo, Japan","institution_ids":["https://openalex.org/I4210125947"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121260471","display_name":"Kensuke Harada","orcid":null},"institutions":[{"id":"https://openalex.org/I11381156","display_name":"Osaka Gakuin University","ror":"https://ror.org/04a8t1e98","country_code":"JP","type":"education","lineage":["https://openalex.org/I11381156"]},{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kensuke Harada","raw_affiliation_strings":["Graduate School of Engineering Science, The University of Osaka, Suita, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7576-756X","affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, The University of Osaka, Suita, Japan","institution_ids":["https://openalex.org/I11381156","https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5155,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.69738607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"11","issue":"2","first_page":"2026","last_page":"2033"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9739000201225281,"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":0.9739000201225281,"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":0.018200000748038292,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.0012000000569969416,"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/grasp","display_name":"GRASP","score":0.9282000064849854},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6773999929428101},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6082000136375427},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5746999979019165},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.542900025844574},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.49639999866485596},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.477400004863739},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.45170000195503235},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3950999975204468}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9282000064849854},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6773999929428101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6743000149726868},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6082000136375427},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5746999979019165},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.542900025844574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5313000082969666},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.49639999866485596},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.477400004863739},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.45170000195503235},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41769999265670776},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3950999975204468},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.31349998712539673},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C17511633","wikidata":"https://www.wikidata.org/wiki/Q830694","display_name":"SMT placement equipment","level":3,"score":0.2987000048160553},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29589998722076416},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.26840001344680786},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2615000009536743},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2025.3645512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3645512","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4414689838886261,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1497854254","https://openalex.org/W1966747088","https://openalex.org/W2296486637","https://openalex.org/W2603737562","https://openalex.org/W2914044489","https://openalex.org/W2945600613","https://openalex.org/W2963654160","https://openalex.org/W2964160067","https://openalex.org/W3002011424","https://openalex.org/W3089966216","https://openalex.org/W3090717212","https://openalex.org/W3201276757","https://openalex.org/W3215761265","https://openalex.org/W4206291425","https://openalex.org/W4210318229","https://openalex.org/W4293732130","https://openalex.org/W4306246346","https://openalex.org/W4360978316","https://openalex.org/W4383108538","https://openalex.org/W4385430665","https://openalex.org/W4388505466","https://openalex.org/W4391407088","https://openalex.org/W4396542427","https://openalex.org/W4402754209","https://openalex.org/W4404520163","https://openalex.org/W4416750463"],"related_works":[],"abstract_inverted_index":{"This":[0],"work":[1],"proposes":[2],"a":[3,32],"learning":[4],"method":[5,99],"to":[6,23,47,111],"accelerate":[7],"robotic":[8],"pick-and-place":[9,33],"planning":[10],"by":[11,70],"predicting":[12],"shared":[13,40,68],"grasps.":[14],"Shared":[15],"grasps":[16,41,69,76,113],"are":[17],"defined":[18],"as":[19,51],"grasp":[20,43,101],"poses":[21],"feasible":[22,75],"both":[24,78],"the":[25,52,58,72,92,122],"initial":[26],"and":[27,89,108,114],"goal":[28],"object":[29,79],"configurations":[30],"in":[31],"task.":[34],"Traditional":[35],"analytical":[36],"methods":[37],"for":[38],"solving":[39],"evaluate":[42],"candidates":[44,88],"separately,":[45],"leading":[46],"substantial":[48],"computational":[49],"overhead":[50],"candidate":[53],"set":[54],"grows.":[55],"To":[56],"overcome":[57],"limitation,":[59],"we":[60],"introduce":[61],"an":[62],"Energy-Based":[63],"Model":[64],"(EBM)":[65],"that":[66,97,118],"predicts":[67],"combining":[71],"energies":[73],"of":[74,86],"at":[77],"poses.":[80],"The":[81],"formulation":[82],"enables":[83],"early":[84],"identification":[85],"promising":[87],"significantly":[90],"reduces":[91],"search":[93],"space.":[94],"Experiments":[95],"show":[96],"our":[98],"improves":[100],"selection":[102],"performance,":[103],"offers":[104],"higher":[105],"data":[106],"efficiency,":[107],"generalizes":[109],"well":[110],"varying":[112],"table":[115],"heights,":[116],"given":[117],"variations":[119],"fall":[120],"within":[121],"learned":[123],"distributions.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-12-25T00:00:00"}
