{"id":"https://openalex.org/W4399601318","doi":"https://doi.org/10.1109/lra.2024.3414265","title":"Learning Rearrangement Manipulation via Scene Prediction in Point Cloud","display_name":"Learning Rearrangement Manipulation via Scene Prediction in Point Cloud","publication_year":2024,"publication_date":"2024-06-13","ids":{"openalex":"https://openalex.org/W4399601318","doi":"https://doi.org/10.1109/lra.2024.3414265"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3414265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3414265","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/A5042342752","display_name":"Anji Ma","orcid":"https://orcid.org/0000-0001-7470-0155"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anji Ma","raw_affiliation_strings":["School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7470-0155","affiliations":[{"raw_affiliation_string":"School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064672242","display_name":"Xingguang Duan","orcid":"https://orcid.org/0000-0002-9640-4928"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingguang Duan","raw_affiliation_strings":["School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9640-4928","affiliations":[{"raw_affiliation_string":"School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06466203,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"12","first_page":"11090","last_page":"11097"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.989300012588501,"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"}},"topics":[{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.989300012588501,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9473000168800354,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7449589967727661},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5669616460800171},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5135369300842285},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.46719691157341003},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4351925253868103},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18963614106178284},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10420581698417664},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.051627933979034424}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7449589967727661},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5669616460800171},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5135369300842285},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.46719691157341003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4351925253868103},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18963614106178284},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10420581698417664},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.051627933979034424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3414265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3414265","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":[],"awards":[{"id":"https://openalex.org/G7282123152","display_name":null,"funder_award_id":"62073043","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2058535340","https://openalex.org/W2337977475","https://openalex.org/W2528489519","https://openalex.org/W2796426482","https://openalex.org/W2962872206","https://openalex.org/W2963654160","https://openalex.org/W2986303149","https://openalex.org/W3174902251","https://openalex.org/W3184955535","https://openalex.org/W4385660512","https://openalex.org/W6636212180","https://openalex.org/W6745420753","https://openalex.org/W6748392304","https://openalex.org/W6756256016","https://openalex.org/W6756908582","https://openalex.org/W6760405395","https://openalex.org/W6763422710","https://openalex.org/W6784607570","https://openalex.org/W6785308759","https://openalex.org/W6789211778","https://openalex.org/W6801810553","https://openalex.org/W6802414455","https://openalex.org/W6843759960"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W3150465815","https://openalex.org/W1997222214"],"abstract_inverted_index":{"Predicting":[0],"scene":[1,40,90],"evolution":[2],"conditioned":[3],"on":[4,20,117,185],"robotic":[5],"actions":[6,24,59,78,141],"is":[7,54],"a":[8,39,72,118,148,186],"vital":[9],"technique":[10],"in":[11,60,154,161],"modeling":[12],"robot":[13,46,76,137],"manipulations.":[14,62],"Previous":[15],"studies":[16],"have":[17],"primarily":[18],"focused":[19],"learning":[21],"spatiotemporally":[22],"continuous":[23],"like":[25,105],"Cartesian":[26],"displacements,":[27],"thus":[28],"applying":[29],"them":[30],"to":[31,56,79,176],"planar-pushing":[32],"tasks.":[33],"In":[34],"this":[35],"letter,":[36],"we":[37],"propose":[38],"prediction":[41,91],"model":[42,64,87,115,133],"that":[43,131,169],"learns":[44,89],"higher-level":[45],"actions,":[47],"such":[48,58],"as":[49],"grasping":[50,138,162],"and":[51,53,75,96,139,142,163,181],"pick-and-place,":[52],"applicable":[55],"planning":[57,150],"rearrangement":[61,164],"The":[63,86],"takes":[65],"partially":[66],"observed":[67],"point":[68,81,93,155],"clouds":[69,82,156],"(e.g.,":[70],"from":[71],"single":[73],"camera)":[74],"pick-and-place":[77,140],"predict":[80],"of":[83,102,188],"future":[84],"scenes.":[85],"directly":[88,174],"using":[92],"cloud":[94],"observation":[95],"representation,":[97],"without":[98,179],"requiring":[99],"prior":[100],"knowledge":[101],"object":[103],"properties":[104],"cad":[106],"models,":[107],"pose,":[108],"or":[109],"instance":[110],"segmentation.":[111],"We":[112],"train":[113],"the":[114,158],"only":[116],"synthetic":[119],"dataset":[120],"acquired":[121],"entirely":[122],"automatically":[123],"with":[124],"minimal":[125],"human":[126],"intervention.":[127],"Our":[128],"experiments":[129],"validate":[130],"our":[132,170],"can":[134,172],"substantially":[135],"learn":[136],"show":[143,168,182],"that,":[144],"when":[145],"integrated":[146],"into":[147],"sample-based":[149],"framework,":[151],"predicting":[152],"scenes":[153],"outperforms":[157],"image-based":[159],"baseline":[160],"manipulation.":[165],"Moreover,":[166],"results":[167],"method":[171],"be":[173],"transferred":[175],"real-world":[177],"environments":[178],"fine-tuning":[180],"promising":[183],"performance":[184],"collection":[187],"18":[189],"household":[190],"objects.":[191]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
