{"id":"https://openalex.org/W3004360048","doi":"https://doi.org/10.1109/iros40897.2019.8968547","title":"Optimal Temporal Logic Planning for Multi-Robot Systems in Uncertain Semantic Maps","display_name":"Optimal Temporal Logic Planning for Multi-Robot Systems in Uncertain Semantic Maps","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3004360048","doi":"https://doi.org/10.1109/iros40897.2019.8968547","mag":"3004360048"},"language":"en","primary_location":{"id":"doi:10.1109/iros40897.2019.8968547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8968547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5014874021","display_name":"Yiannis Kantaros","orcid":"https://orcid.org/0000-0002-0257-7378"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiannis Kantaros","raw_affiliation_strings":["University of Pennsylvania, Philadelphia,Department of Electrical and Systems Engineering,PA,USA,19104","Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia,Department of Electrical and Systems Engineering,PA,USA,19104","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029243115","display_name":"George J. Pappas","orcid":"https://orcid.org/0000-0001-9081-0637"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George J. Pappas","raw_affiliation_strings":["University of Pennsylvania, Philadelphia,Department of Electrical and Systems Engineering,PA,USA,19104","Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia,Department of Electrical and Systems Engineering,PA,USA,19104","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":1.0158,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8155193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4127","last_page":"4132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998000264167786,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998000264167786,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.9987000226974487,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9983000159263611,"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":0.7261761426925659},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6398283839225769},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6391249895095825},{"id":"https://openalex.org/keywords/probabilistic-roadmap","display_name":"Probabilistic roadmap","score":0.5752257108688354},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.5471774339675903},{"id":"https://openalex.org/keywords/workspace","display_name":"Workspace","score":0.5282902717590332},{"id":"https://openalex.org/keywords/linear-temporal-logic","display_name":"Linear temporal logic","score":0.508607029914856},{"id":"https://openalex.org/keywords/semantic-mapping","display_name":"Semantic mapping","score":0.501279354095459},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4923008680343628},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.48889532685279846},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.4670853614807129},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4402892291545868},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.4243905544281006},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4243046045303345},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4119725823402405},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.38104501366615295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38091909885406494},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.356295108795166}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7261761426925659},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6398283839225769},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6391249895095825},{"id":"https://openalex.org/C2778803389","wikidata":"https://www.wikidata.org/wiki/Q7246866","display_name":"Probabilistic roadmap","level":4,"score":0.5752257108688354},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5471774339675903},{"id":"https://openalex.org/C58581272","wikidata":"https://www.wikidata.org/wiki/Q12741163","display_name":"Workspace","level":3,"score":0.5282902717590332},{"id":"https://openalex.org/C4777664","wikidata":"https://www.wikidata.org/wiki/Q1536492","display_name":"Linear temporal logic","level":2,"score":0.508607029914856},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.501279354095459},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4923008680343628},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48889532685279846},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.4670853614807129},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4402892291545868},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.4243905544281006},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4243046045303345},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4119725823402405},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.38104501366615295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38091909885406494},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.356295108795166},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros40897.2019.8968547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8968547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"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":22,"referenced_works":["https://openalex.org/W1498432697","https://openalex.org/W2038469972","https://openalex.org/W2059470663","https://openalex.org/W2073548775","https://openalex.org/W2077578897","https://openalex.org/W2087179560","https://openalex.org/W2103052138","https://openalex.org/W2141789581","https://openalex.org/W2157807654","https://openalex.org/W2168992242","https://openalex.org/W2235884325","https://openalex.org/W2381901500","https://openalex.org/W2511015524","https://openalex.org/W2571161957","https://openalex.org/W2624912704","https://openalex.org/W2739423245","https://openalex.org/W2743098504","https://openalex.org/W2913325211","https://openalex.org/W2963117388","https://openalex.org/W3105174872","https://openalex.org/W3151793825","https://openalex.org/W6739554287"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2005087563","https://openalex.org/W1581933381","https://openalex.org/W1993546951","https://openalex.org/W4390828597","https://openalex.org/W4362598481","https://openalex.org/W3176904019","https://openalex.org/W4383108436","https://openalex.org/W3004360048"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"a":[3,56,98,115],"multi-robot":[4],"motion":[5,117],"planning":[6,157],"problem":[7],"in":[8,38,43,50],"probabilistic":[9,88],"maps":[10],"obtained":[11],"by":[12,33,60,78,134],"semantic":[13,57],"simultaneous":[14],"localization":[15],"and":[16,66,87,132,148],"mapping":[17],"(SLAM).":[18],"The":[19],"goal":[20],"of":[21,41],"the":[22,39,44,47,93,109,124,145,151],"robots":[23,48],"is":[24,127],"to":[25,84],"accomplish":[26],"complex":[27],"collaborative":[28],"high":[29],"level":[30],"tasks":[31],"captured":[32],"global":[34],"temporal":[35],"logic":[36],"specifications":[37],"presence":[40],"uncertainty":[42,86],"workspace.":[45],"Specifically,":[46],"operate":[49],"an":[51],"unknown":[52],"environment":[53],"modeled":[54],"as":[55],"map":[58],"determined":[59],"Gaussian":[61],"distributions":[62,69],"over":[63,70],"landmark":[64,71],"positions":[65],"arbitrary":[67],"discrete":[68],"classes.":[72],"We":[73,96,138],"extend":[74],"Linear":[75],"Temporal":[76],"Logic":[77],"including":[79],"information-based":[80],"predicates":[81],"allowing":[82],"us":[83],"incorporate":[85],"satisfaction":[89],"requirements":[90],"directly":[91],"into":[92],"task":[94,111],"specification.":[95],"propose":[97],"new":[99],"highly":[100],"scalable":[101],"sampling-based":[102],"approach":[103],"that":[104,107,123,143,150],"synthesizes":[105],"paths":[106],"satisfy":[108],"assigned":[110],"specification":[112],"while":[113],"minimizing":[114],"user-specified":[116],"cost":[118],"function.":[119],"Finally,":[120],"we":[121],"show":[122,149],"proposed":[125,152],"algorithm":[126,153],"probabilistically":[128],"complete,":[129],"asymptotically":[130],"optimal":[131],"supported":[133],"convergence":[135],"rate":[136],"bounds.":[137],"provide":[139],"extensive":[140],"simulation":[141],"results":[142],"corroborate":[144],"theoretical":[146],"analysis":[147],"can":[154],"address":[155],"large-scale":[156],"tasks.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}