{"id":"https://openalex.org/W4416335641","doi":"https://doi.org/10.3724/sp.j.1089.2024.20120","title":"Autonomous Exploration and Object Perception Algorithm for a Robot Based on Reinforcement Learning","display_name":"Autonomous Exploration and Object Perception Algorithm for a Robot Based on Reinforcement Learning","publication_year":2024,"publication_date":"2024-11-01","ids":{"openalex":"https://openalex.org/W4416335641","doi":"https://doi.org/10.3724/sp.j.1089.2024.20120"},"language":"en","primary_location":{"id":"doi:10.3724/sp.j.1089.2024.20120","doi":"https://doi.org/10.3724/sp.j.1089.2024.20120","is_oa":true,"landing_page_url":"https://doi.org/10.3724/sp.j.1089.2024.20120","pdf_url":"https://www.sciengine.com/doi/pdf/B2223DB635D943518516EF979B3D97F6","source":{"id":"https://openalex.org/S4210220856","display_name":"Journal of Computer-Aided Design & Computer Graphics","issn_l":"1003-9775","issn":["1003-9775"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":"https://openalex.org/P4310319982","host_organization_name":"Science Press","host_organization_lineage":["https://openalex.org/P4310319982"],"host_organization_lineage_names":["Science Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer-Aided Design & Computer Graphics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.sciengine.com/doi/pdf/B2223DB635D943518516EF979B3D97F6","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Guan Wu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103662131","display_name":"Xia Xi","orcid":"https://orcid.org/0000-0002-3396-9243","observed_orcids":["https://orcid.org/0000-0002-3396-9243"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xi Xia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012388026","display_name":"Hezhi Cao","orcid":"https://orcid.org/0000-0003-4760-0743","observed_orcids":["https://orcid.org/0000-0003-4760-0743"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hezhi Cao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100635702","display_name":"Ligang Liu","orcid":"https://orcid.org/0000-0003-4352-1431","observed_orcids":["https://orcid.org/0000-0003-4352-1431","https://orcid.org/0009-0004-9169-9757"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ligang Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21093393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"11","first_page":"1852","last_page":"1862"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6963000297546387,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6963000297546387,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.298799991607666,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10653","display_name":"Robot Manipulation and Learning","score":0.0008999999845400453,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autonomous-robot-exploration","display_name":"autonomous robot exploration","score":0.7590000033378601},{"id":"https://openalex.org/keywords/object-perception","display_name":"object perception","score":0.8949999809265137},{"id":"https://openalex.org/keywords/deep-reinforcement-learning","display_name":"deep reinforcement learning","score":0.890999972820282},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"SLAM","score":0.9549999833106995},{"id":"https://openalex.org/keywords/path-planning","display_name":"path planning","score":0.8019999861717224},{"id":"https://openalex.org/keywords/semantic-scene-understanding","display_name":"semantic scene understanding","score":0.5299999713897705}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6988999843597412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6983000040054321},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.684499979019165},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6542999744415283},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6018999814987183},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5758000016212463},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5479000210762024},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5461999773979187},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5060999989509583},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4194999933242798},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.37130001187324524},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.3700000047683716},{"id":"https://openalex.org/C2778835581","wikidata":"https://www.wikidata.org/wiki/Q2916098","display_name":"Autonomous robot","level":4,"score":0.3598000109195709},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.35690000653266907},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.31380000710487366},{"id":"https://openalex.org/C2779188883","wikidata":"https://www.wikidata.org/wiki/Q82446","display_name":"Global Map","level":3,"score":0.3127000033855438},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.3061999976634979},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.29679998755455017},{"id":"https://openalex.org/C162947575","wikidata":"https://www.wikidata.org/wiki/Q2005645","display_name":"Social robot","level":5,"score":0.2732999920845032},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2727000117301941},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C188888258","wikidata":"https://www.wikidata.org/wiki/Q7353390","display_name":"Robot learning","level":4,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3724/sp.j.1089.2024.20120","doi":"https://doi.org/10.3724/sp.j.1089.2024.20120","is_oa":true,"landing_page_url":"https://doi.org/10.3724/sp.j.1089.2024.20120","pdf_url":"https://www.sciengine.com/doi/pdf/B2223DB635D943518516EF979B3D97F6","source":{"id":"https://openalex.org/S4210220856","display_name":"Journal of Computer-Aided Design & Computer Graphics","issn_l":"1003-9775","issn":["1003-9775"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":"https://openalex.org/P4310319982","host_organization_name":"Science Press","host_organization_lineage":["https://openalex.org/P4310319982"],"host_organization_lineage_names":["Science Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer-Aided Design & Computer Graphics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3724/sp.j.1089.2024.20120","doi":"https://doi.org/10.3724/sp.j.1089.2024.20120","is_oa":true,"landing_page_url":"https://doi.org/10.3724/sp.j.1089.2024.20120","pdf_url":"https://www.sciengine.com/doi/pdf/B2223DB635D943518516EF979B3D97F6","source":{"id":"https://openalex.org/S4210220856","display_name":"Journal of Computer-Aided Design & Computer Graphics","issn_l":"1003-9775","issn":["1003-9775"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":"https://openalex.org/P4310319982","host_organization_name":"Science Press","host_organization_lineage":["https://openalex.org/P4310319982"],"host_organization_lineage_names":["Science Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer-Aided Design & Computer Graphics","raw_type":"journal-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416335641.pdf","grobid_xml":"https://content.openalex.org/works/W4416335641.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,32,43,63,120,124,127,137],"efficiently":[3],"perceive":[4],"objects":[5],"in":[6,67,175,188,209],"the":[7,29,34,41,55,65,101,107,118,122,125,131,146,151,154,163,168,196],"exploration":[8,15,50,81,88,109,148],"of":[9,40,153,203],"unknown":[10],"indoor":[11],"scenes,":[12],"an":[13],"autonomous":[14],"and":[16,37,48,77,86,93,166,177,183,207,213],"object":[17,200],"perception":[18,201,219],"algorithm":[19,58,198],"for":[20,142,221],"a":[21,45,60,97,112,139],"robot":[22,30,123,143,157],"is":[23,72,135],"proposed.":[24],"Using":[25],"deep":[26],"reinforcement":[27,68],"learning,":[28],"learns":[31],"use":[33],"layout":[35],"rules":[36],"semantic":[38],"information":[39],"scene":[42],"obtain":[44],"more":[46],"efficient":[47],"high-quality":[49],"strategy":[51],"through":[52],"interaction":[53],"with":[54,181],"environment.":[56,191],"The":[57,90,170,192],"uses":[59],"modular":[61],"framework":[62],"conquer":[64],"difficulty":[66],"learning":[69],"training,":[70],"which":[71],"divided":[73],"into":[74],"simultaneous":[75,91],"localization":[76,92],"mapping":[78,94],"module,":[79,82],"global":[80,108],"path":[83,132],"planning":[84,133],"module":[85,95,110,134,149],"local":[87,147,164],"module.":[89],"construct":[96],"map":[98,119,165],"based":[99,116,161],"on":[100,117,156,162],"data":[102],"obtained":[103],"by":[104],"sensors.":[105],"Then":[106],"decides":[111],"long":[113],"term":[114],"goal":[115],"guide":[121],"area":[126],"be":[128],"explored.":[129],"Next,":[130],"employed":[136],"generate":[138],"collision-free":[140],"trajectory":[141],"navigation.":[144],"And":[145],"plans":[150],"orientation":[152],"sensor":[155],"at":[158],"each":[159],"step":[160],"updates":[167],"map.":[169],"comparative":[171],"experiments":[172],"are":[173],"conducted":[174],"Gibson":[176],"Matterport3D":[178],"public":[179],"datasets":[180],"SC":[182],"ANS":[184],"two":[185],"advanced":[186],"algorithms":[187],"Habitat":[189],"simulation":[190],"results":[193],"show":[194],"that":[195],"proposed":[197],"has":[199],"rates":[202],"0.942,":[204],"0.866,":[205],"0.652":[206],"0.506":[208],"small,":[210],"medium,":[211],"large":[212],"extra-large":[214],"scenes":[215],"respectively,":[216],"demonstrating":[217],"good":[218],"performance":[220],"scenes.":[222]},"counts_by_year":[],"updated_date":"2026-09-27T08:07:27.782135","created_date":"2025-11-19T00:00:00"}