{"id":"https://openalex.org/W3211815580","doi":"https://doi.org/10.1109/icra46639.2022.9812256","title":"Barrier Forming: Separating Polygonal Sets with Minimum Number of Lines","display_name":"Barrier Forming: Separating Polygonal Sets with Minimum Number of Lines","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W3211815580","doi":"https://doi.org/10.1109/icra46639.2022.9812256","mag":"3211815580"},"language":"en","primary_location":{"id":"doi:10.1109/icra46639.2022.9812256","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812256","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 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/A5046738416","display_name":"Si Wei Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Si Wei Feng","raw_affiliation_strings":["Rutgers, the State University of New Jersey,Department of Computer Science,Piscataway,NJ,USA","Department of Computer Science, Rutgers, the State University of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey,Department of Computer Science,Piscataway,NJ,USA","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Department of Computer Science, Rutgers, the State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076210154","display_name":"Jingjin Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingjin Yu","raw_affiliation_strings":["Rutgers, the State University of New Jersey,Department of Computer Science,Piscataway,NJ,USA","Department of Computer Science, Rutgers, the State University of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey,Department of Computer Science,Piscataway,NJ,USA","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Department of Computer Science, Rutgers, the State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102322142"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"5828","last_page":"5834"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9973000288009644,"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":0.9973000288009644,"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/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.8313071727752686},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6232863664627075},{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.6120250821113586},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5898972749710083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5840805172920227},{"id":"https://openalex.org/keywords/plane","display_name":"Plane (geometry)","score":0.5597469806671143},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42254048585891724},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.39266565442085266},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38416463136672974},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3089449405670166},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.17377018928527832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14684346318244934}],"concepts":[{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.8313071727752686},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6232863664627075},{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.6120250821113586},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5898972749710083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5840805172920227},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.5597469806671143},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42254048585891724},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.39266565442085266},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38416463136672974},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3089449405670166},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.17377018928527832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14684346318244934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra46639.2022.9812256","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812256","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6612688412","display_name":null,"funder_award_id":"IIS-1845888,IIS-2132972","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W37461142","https://openalex.org/W1497515831","https://openalex.org/W1576174958","https://openalex.org/W1581842928","https://openalex.org/W1589059037","https://openalex.org/W1589281261","https://openalex.org/W1816496481","https://openalex.org/W2015469394","https://openalex.org/W2017136493","https://openalex.org/W2036809398","https://openalex.org/W2055504162","https://openalex.org/W2074574297","https://openalex.org/W2087787973","https://openalex.org/W2105115265","https://openalex.org/W2109518636","https://openalex.org/W2120488355","https://openalex.org/W2165471099","https://openalex.org/W2501758057","https://openalex.org/W2795559577","https://openalex.org/W2947905785","https://openalex.org/W2961484741","https://openalex.org/W3006248364","https://openalex.org/W3040018106","https://openalex.org/W3048972113","https://openalex.org/W3129496379","https://openalex.org/W3138865866","https://openalex.org/W6601543414","https://openalex.org/W6633084826","https://openalex.org/W6635470366"],"related_works":["https://openalex.org/W2019903130","https://openalex.org/W2011903683","https://openalex.org/W4386442742","https://openalex.org/W2353000084","https://openalex.org/W4205730002","https://openalex.org/W2942906518","https://openalex.org/W2356676145","https://openalex.org/W2371953206","https://openalex.org/W2349543044","https://openalex.org/W2093858167"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,73],"carry":[4],"out":[5],"structural":[6],"and":[7,142],"al-gorithmic":[8],"studies":[9],"of":[10,13,20,29,42,53,80,86,95,101,139,154],"a":[11,56,144],"problem":[12,37,68,94],"barrier":[14,96,108],"forming:":[15],"selecting":[16],"the":[17,34,39,77,89,92,128,132,137,148,152],"minimum":[18,78,99],"number":[19,79,100],"straight":[21],"line":[22,43,102],"segments":[23],"(barriers)":[24],"that":[25],"separate":[26,83],"several":[27],"sets":[28,85,114,119],"mutually":[30],"disjoint":[31],"objects":[32],"in":[33,55,88],"plane.":[35,90],"The":[36,67],"models":[38],"optimal":[40,129],"placement":[41],"sensors":[44],"(e.g.,":[45,63],"infrared":[46],"laser":[47],"beams)":[48],"for":[49,60,110,126,131,147],"isolating":[50],"many":[51],"types":[52],"regions":[54],"pair-":[57],"wise":[58],"manner":[59],"practical":[61],"purposes":[62],"guarding":[64],"against":[65],"intrusions).":[66],"is":[69],"NP-hard":[70],"even":[71],"if":[72],"want":[74],"to":[75,82],"find":[76],"lines":[81],"two":[84,134],"points":[87],"Under":[91],"umbrella":[93],"forming":[97,109],"with":[98,115,120,136],"segments,":[103],"three":[104],"settings":[105,135],"are":[106],"examined:":[107],"point":[111,113],"sets,":[112],"polygonal":[116,118,121],"obstacles,":[117],"obstacles.":[122],"We":[123,150],"describe":[124],"methods":[125,156],"computing":[127],"solution":[130,146],"first":[133],"assistance":[138],"mathematical":[140],"programming,":[141],"provide":[143],"2-OPT":[145],"third.":[149],"demonstrate":[151],"effectiveness":[153],"our":[155],"through":[157],"extensive":[158],"simulations.":[159]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}