{"id":"https://openalex.org/W4383108730","doi":"https://doi.org/10.1109/icra48891.2023.10161476","title":"Learning Augmented, Multi-Robot Long-Horizon Navigation in Partially Mapped Environments","display_name":"Learning Augmented, Multi-Robot Long-Horizon Navigation in Partially Mapped Environments","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383108730","doi":"https://doi.org/10.1109/icra48891.2023.10161476"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10161476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10161476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5055003937","display_name":"Abhish Khanal","orcid":null},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhish Khanal","raw_affiliation_strings":["George Mason University,Department of Computer Science,Fairfax,VA,USA,22030"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University,Department of Computer Science,Fairfax,VA,USA,22030","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042000667","display_name":"G. Stein","orcid":"https://orcid.org/0000-0003-1981-4154"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory J. Stein","raw_affiliation_strings":["George Mason University,Department of Computer Science,Fairfax,VA,USA,22030"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University,Department of Computer Science,Fairfax,VA,USA,22030","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.6534,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66951096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"10167","last_page":"10173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9973999857902527,"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":0.9973999857902527,"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":0.9965000152587891,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9965000152587891,"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/computer-science","display_name":"Computer science","score":0.7144505977630615},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.7053424119949341},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.6437860727310181},{"id":"https://openalex.org/keywords/planner","display_name":"Planner","score":0.6349886059761047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.623818039894104},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.5994384288787842},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4784150719642639},{"id":"https://openalex.org/keywords/time-horizon","display_name":"Time horizon","score":0.4622739255428314},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.44703003764152527},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.41878488659858704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41809818148612976},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.4163036644458771},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4142829179763794},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4117283821105957},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3881070017814636},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3467181921005249},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.2931232452392578},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.19335567951202393},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.13875088095664978},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08338949084281921}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7144505977630615},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.7053424119949341},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.6437860727310181},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.6349886059761047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.623818039894104},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.5994384288787842},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4784150719642639},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.4622739255428314},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.44703003764152527},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.41878488659858704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41809818148612976},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.4163036644458771},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4142829179763794},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4117283821105957},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3881070017814636},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3467181921005249},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.2931232452392578},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.19335567951202393},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.13875088095664978},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08338949084281921},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10161476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10161476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W329015778","https://openalex.org/W1539216098","https://openalex.org/W1560074431","https://openalex.org/W1579579904","https://openalex.org/W1886379263","https://openalex.org/W1908253641","https://openalex.org/W1957906757","https://openalex.org/W1966213627","https://openalex.org/W1976195538","https://openalex.org/W1977655452","https://openalex.org/W1992787855","https://openalex.org/W2020426055","https://openalex.org/W2037034267","https://openalex.org/W2096145798","https://openalex.org/W2103863840","https://openalex.org/W2107667896","https://openalex.org/W2168359464","https://openalex.org/W2171084228","https://openalex.org/W2290743114","https://openalex.org/W2294192315","https://openalex.org/W2395575420","https://openalex.org/W2405686381","https://openalex.org/W2568597750","https://openalex.org/W2754517384","https://openalex.org/W2768629321","https://openalex.org/W2843387146","https://openalex.org/W2899201819","https://openalex.org/W2937310911","https://openalex.org/W2950279385","https://openalex.org/W2951660448","https://openalex.org/W3206931309","https://openalex.org/W4288280051","https://openalex.org/W6633472260","https://openalex.org/W6634752865","https://openalex.org/W6640044251","https://openalex.org/W6640867910","https://openalex.org/W6684973485","https://openalex.org/W6697106730","https://openalex.org/W6746015766","https://openalex.org/W6755934310","https://openalex.org/W6808026086"],"related_works":["https://openalex.org/W2096013579","https://openalex.org/W1589140671","https://openalex.org/W1760611253","https://openalex.org/W52153049","https://openalex.org/W2951545791","https://openalex.org/W1515117609","https://openalex.org/W2160491016","https://openalex.org/W2294884454","https://openalex.org/W4323315247","https://openalex.org/W3169161914"],"abstract_inverted_index":{"We":[0,79],"present":[1],"a":[2,13,17,40,54,113],"novel":[3],"approach":[4,96],"for":[5,12],"efficient":[6],"and":[7,43,101,112],"reliable":[8],"goal-directed":[9],"long-horizon":[10],"navigation":[11],"multi-robot":[14,86],"team":[15],"in":[16,31,82,88],"structured,":[18],"unknown":[19,25],"environment":[20],"by":[21],"predicting":[22],"statistics":[23],"of":[24,70],"space.":[26],"Building":[27],"on":[28],"recent":[29],"work":[30],"learning-augmented":[32],"model":[33],"based":[34],"planning":[35,111],"under":[36],"uncertainty,":[37],"we":[38,92],"introduce":[39],"high-level":[41],"state":[42],"action":[44],"abstraction":[45],"that":[46,94],"lets":[47],"us":[48],"approximate":[49],"the":[50,76],"challenging":[51],"Dec-POMDP":[52],"into":[53],"tractable":[55],"stochastic":[56],"MDP.":[57],"Our":[58],"Multi-Robot":[59],"Learning":[60],"over":[61],"Subgoals":[62],"Planner":[63],"(MR-LSP)":[64],"guides":[65],"agents":[66],"towards":[67],"coordinated":[68],"exploration":[69],"regions":[71],"more":[72],"likely":[73],"to":[74],"reach":[75],"unseen":[77],"goal.":[78],"demonstrate":[80],"improvement":[81],"cost":[83,106],"against":[84],"other":[85],"strategies;":[87],"simulated":[89],"office-like":[90],"environments,":[91],"show":[93],"our":[95],"saves":[97],"13.29%":[98],"(2":[99],"robot)":[100,104],"4.6%":[102],"(3":[103],"average":[105],"versus":[107],"standard":[108],"non-learned":[109],"optimistic":[110],"learning-informed":[114],"baseline.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}