{"id":"https://openalex.org/W3145622882","doi":"https://doi.org/10.1109/icara51699.2021.9376498","title":"Online Area Covering Robot in Unknown Dynamic Environments","display_name":"Online Area Covering Robot in Unknown Dynamic Environments","publication_year":2021,"publication_date":"2021-02-04","ids":{"openalex":"https://openalex.org/W3145622882","doi":"https://doi.org/10.1109/icara51699.2021.9376498","mag":"3145622882"},"language":"en","primary_location":{"id":"doi:10.1109/icara51699.2021.9376498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icara51699.2021.9376498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th International Conference on Automation, Robotics and Applications (ICARA)","raw_type":"proceedings-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/A5033813742","display_name":"Olimpiya Saha","orcid":"https://orcid.org/0000-0002-6980-1418"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Olimpiya Saha","raw_affiliation_strings":["Advanced AI Team, LG America Research Lab, Santa Clara, USA"],"affiliations":[{"raw_affiliation_string":"Advanced AI Team, LG America Research Lab, Santa Clara, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011809025","display_name":"Guohua Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guohua Ren","raw_affiliation_strings":["Advanced AI Team, LG America Research Lab, Santa Clara, USA"],"affiliations":[{"raw_affiliation_string":"Advanced AI Team, LG America Research Lab, Santa Clara, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000190599","display_name":"Javad Heydari","orcid":"https://orcid.org/0000-0001-9671-2982"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Javad Heydari","raw_affiliation_strings":["Advanced AI Team, LG America Research Lab, Santa Clara, USA"],"affiliations":[{"raw_affiliation_string":"Advanced AI Team, LG America Research Lab, Santa Clara, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110670519","display_name":"V. Ganapathy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Viswanath Ganapathy","raw_affiliation_strings":["Advanced AI Team, LG America Research Lab, Santa Clara, USA"],"affiliations":[{"raw_affiliation_string":"Advanced AI Team, LG America Research Lab, Santa Clara, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108916424","display_name":"Mohak Shah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohak Shah","raw_affiliation_strings":["Advanced AI Team, LG America Research Lab, Santa Clara, USA"],"affiliations":[{"raw_affiliation_string":"Advanced AI Team, LG America Research Lab, Santa Clara, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5033813742"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8496,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77188137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"38","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9993000030517578,"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":0.9993000030517578,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9983999729156494,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.7931976318359375},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7340874671936035},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6811994910240173},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.6298993229866028},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5935020446777344},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5633394718170166},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5341419577598572},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.44937729835510254},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.44305533170700073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4381345510482788},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.42713162302970886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7931976318359375},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7340874671936035},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6811994910240173},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.6298993229866028},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5935020446777344},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5633394718170166},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5341419577598572},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.44937729835510254},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.44305533170700073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4381345510482788},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.42713162302970886},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icara51699.2021.9376498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icara51699.2021.9376498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th International Conference on Automation, Robotics and Applications (ICARA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W41554520","https://openalex.org/W101508493","https://openalex.org/W1191599655","https://openalex.org/W1522301498","https://openalex.org/W1590932131","https://openalex.org/W1607748423","https://openalex.org/W1970499532","https://openalex.org/W2001478433","https://openalex.org/W2046376809","https://openalex.org/W2089344586","https://openalex.org/W2121863487","https://openalex.org/W2132911351","https://openalex.org/W2145339207","https://openalex.org/W2156126164","https://openalex.org/W2761873684","https://openalex.org/W2766249432","https://openalex.org/W2792427381","https://openalex.org/W2848676021","https://openalex.org/W2891816981","https://openalex.org/W2898153099","https://openalex.org/W2964043796","https://openalex.org/W2964121744","https://openalex.org/W2964291307","https://openalex.org/W6744838376"],"related_works":["https://openalex.org/W2794103424","https://openalex.org/W4245435724","https://openalex.org/W1996530509","https://openalex.org/W3028317537","https://openalex.org/W2389515972","https://openalex.org/W2055301889","https://openalex.org/W1505959757","https://openalex.org/W2376554934","https://openalex.org/W2077790809","https://openalex.org/W2394276631"],"abstract_inverted_index":{"Autonomous":[0],"area":[1,23],"covering":[2,24],"robots":[3,19],"are":[4],"being":[5],"increasingly":[6],"deployed":[7,179],"in":[8,58,92,101,117,174,182],"residential":[9],"and":[10,45,104],"commercial":[11],"settings":[12],"for":[13,89,180],"a":[14],"variety":[15],"of":[16,32,112,124,141],"purposes.":[17],"These":[18],"usually":[20],"employ":[21],"universal":[22],"algorithms":[25,34,68,88,116],"to":[26,52,71,137,157],"cover":[27,158],"indoor":[28],"environments.":[29],"The":[30,122],"performance":[31,77,111,123],"such":[33],"heavily":[35],"depends":[36],"on":[37],"room":[38],"geometry":[39],"as":[40,42],"well":[41],"obstacle":[43],"location,":[44],"often":[46],"suffers":[47],"from":[48],"significant":[49],"overlap":[50],"leading":[51],"inordinately":[53],"long":[54],"coverage":[55,91,115,181],"time,":[56],"especially":[57],"realistic":[59],"unknown":[60,93,160,184],"environments":[61,94,103,118,161,176,185],"with":[62,95,119,130,134,162,186],"dynamic":[63,97,120,135],"obstacles.":[64,98,121],"Hence,":[65],"deploying":[66],"smarter":[67],"that":[69,170],"adapt":[70],"the":[72,76,109,131,139,142,152],"environment":[73],"can":[74,177],"improve":[75],"significantly.":[78],"In":[79],"this":[80],"study,":[81],"we":[82,107,168],"explore":[83],"deep":[84],"reinforcement":[85],"learning":[86,151],"(RL)":[87],"efficient":[90],"multiple":[96],"Through":[99],"experiments":[100],"grid-based":[102],"Gazebo":[105],"simulator,":[106],"demonstrate":[108,138],"superior":[110],"RL":[113,125,154,171],"based":[114,126],"algorithm":[127,133],"is":[128],"compared":[129],"BA*":[132],"re-planning":[136],"advantages":[140],"former":[143],"over":[144],"one-shot":[145],"algorithms.":[146],"Further,":[147],"by":[148],"employing":[149],"transfer":[150],"trained":[153,173],"agent":[155],"learns":[156],"unseen":[159],"minimal":[163],"additional":[164,188],"sample":[165,189],"complexity.":[166,190],"Importantly,":[167],"show":[169],"agents":[172],"smaller":[175],"be":[178],"larger":[183],"marginal":[187]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
