{"id":"https://openalex.org/W2963160518","doi":"https://doi.org/10.1109/iros40897.2019.8968503","title":"LEGO: Leveraging Experience in Roadmap Generation for Sampling-Based Planning","display_name":"LEGO: Leveraging Experience in Roadmap Generation for Sampling-Based Planning","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2963160518","doi":"https://doi.org/10.1109/iros40897.2019.8968503","mag":"2963160518"},"language":"en","primary_location":{"id":"doi:10.1109/iros40897.2019.8968503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8968503","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":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1907.09574","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037825401","display_name":"Rahul Kumar","orcid":"https://orcid.org/0000-0002-9287-7197"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rahul Kumar","raw_affiliation_strings":["Indian Institute of Technology,Department of Computer Science,Kharagpur"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Computer Science,Kharagpur","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009506101","display_name":"Aditya Mandalika","orcid":"https://orcid.org/0000-0003-1114-5435"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aditya Mandalika","raw_affiliation_strings":["Indian Institute of Technology,Department of Computer Science,Kharagpur"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Computer Science,Kharagpur","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057995939","display_name":"Sanjiban Choudhury","orcid":"https://orcid.org/0000-0003-2762-8888"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sanjiban Choudhury","raw_affiliation_strings":["Indian Institute of Technology,Department of Computer Science,Kharagpur"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Computer Science,Kharagpur","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077719529","display_name":"Siddhartha S Srinivasa","orcid":"https://orcid.org/0000-0002-5091-106X"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Siddhartha Srinivasa","raw_affiliation_strings":["Indian Institute of Technology,Department of Computer Science,Kharagpur"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Computer Science,Kharagpur","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145894827"],"apc_list":null,"apc_paid":null,"fwci":0.366,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64844982,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1488","last_page":"1495"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.996399998664856,"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":0.996399998664856,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.984499990940094,"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"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.983299970626831,"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":0.7388759851455688},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6906444430351257},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.6829804182052612},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.675364077091217},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5911461710929871},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5263394117355347},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4930438697338104},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4923948049545288},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.48412784934043884},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4575991928577423},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4539494514465332},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.44248074293136597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43060722947120667},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37530484795570374},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3367224335670471},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10980278253555298},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10633379220962524},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09126082062721252}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7388759851455688},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6906444430351257},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.6829804182052612},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.675364077091217},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5911461710929871},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5263394117355347},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4930438697338104},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4923948049545288},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.48412784934043884},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4575991928577423},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4539494514465332},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.44248074293136597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43060722947120667},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37530484795570374},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3367224335670471},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10980278253555298},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10633379220962524},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09126082062721252},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iros40897.2019.8968503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8968503","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"},{"id":"pmh:oai:arXiv.org:1907.09574","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.09574","pdf_url":"https://arxiv.org/pdf/1907.09574","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2963160518","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1907.09574","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1907.09574","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1907.09574","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1907.09574","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.09574","pdf_url":"https://arxiv.org/pdf/1907.09574","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963160518.pdf","grobid_xml":"https://content.openalex.org/works/W2963160518.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W6147906","https://openalex.org/W178999881","https://openalex.org/W181534116","https://openalex.org/W1424654272","https://openalex.org/W1495392417","https://openalex.org/W1532788009","https://openalex.org/W1595414374","https://openalex.org/W1712772804","https://openalex.org/W1937587174","https://openalex.org/W1959608418","https://openalex.org/W1969483458","https://openalex.org/W1971355878","https://openalex.org/W2017001763","https://openalex.org/W2029652111","https://openalex.org/W2038131922","https://openalex.org/W2068911002","https://openalex.org/W2101043416","https://openalex.org/W2107535513","https://openalex.org/W2109212155","https://openalex.org/W2114628632","https://openalex.org/W2115257338","https://openalex.org/W2118356379","https://openalex.org/W2128990851","https://openalex.org/W2142624263","https://openalex.org/W2143996311","https://openalex.org/W2144067986","https://openalex.org/W2154038478","https://openalex.org/W2156459680","https://openalex.org/W2167458557","https://openalex.org/W2188365844","https://openalex.org/W2397499736","https://openalex.org/W2405526757","https://openalex.org/W2467604901","https://openalex.org/W2553756201","https://openalex.org/W2563186568","https://openalex.org/W2569181534","https://openalex.org/W2605102758","https://openalex.org/W2611243847","https://openalex.org/W2883332136","https://openalex.org/W2885010347","https://openalex.org/W2894417726","https://openalex.org/W2922572893","https://openalex.org/W2962758608","https://openalex.org/W2963439114","https://openalex.org/W2964239169","https://openalex.org/W3103834977","https://openalex.org/W6607260878","https://openalex.org/W6629573421","https://openalex.org/W6637540238","https://openalex.org/W6640963894","https://openalex.org/W6682533216","https://openalex.org/W6687045409","https://openalex.org/W6713625716","https://openalex.org/W6720208624","https://openalex.org/W6729895595","https://openalex.org/W6753557484","https://openalex.org/W6765773242"],"related_works":["https://openalex.org/W3004207898","https://openalex.org/W1500643070","https://openalex.org/W3033803035","https://openalex.org/W2161675447","https://openalex.org/W2202985545","https://openalex.org/W2289741470","https://openalex.org/W2961188780","https://openalex.org/W2922204282","https://openalex.org/W3132780644","https://openalex.org/W2065529243","https://openalex.org/W1547744999","https://openalex.org/W2949457334","https://openalex.org/W2562845103","https://openalex.org/W2737443454","https://openalex.org/W2343153154","https://openalex.org/W2767823020","https://openalex.org/W2048721057","https://openalex.org/W1519517979","https://openalex.org/W2000719175","https://openalex.org/W3183167628"],"abstract_inverted_index":{"We":[0,105,164,175],"consider":[1],"the":[2,69,73,93,116,157],"problem":[3],"of":[4,51,95,159,182],"leveraging":[5],"prior":[6,70],"experience":[7],"to":[8,47,61,131,155],"generate":[9],"roadmaps":[10],"in":[11,92],"sampling-based":[12],"motion":[13],"planning.":[14],"A":[15],"desirable":[16],"roadmap":[17],"is":[18,21,46,60,81],"one":[19],"that":[20,35,53,110,121,137],"sparse,":[22],"allowing":[23],"for":[24,173],"fast":[25],"search,":[26],"with":[27,72,118,142],"nodes":[28,52],"spread":[29,150],"out":[30,151],"at":[31],"key":[32],"locations":[33],"such":[34,56],"a":[36,49,57,63,143,160,180],"low-":[37],"cost":[38],"feasible":[39,161],"path":[40,162],"exists.":[41],"An":[42],"increasingly":[43],"popular":[44],"approach":[45],"learn":[48],"distribution":[50],"would":[54],"produce":[55],"roadmap.":[58],"State-of-the-art":[59],"train":[62],"conditional":[64],"variational":[65],"auto-encoder":[66],"(CVAE)":[67],"on":[68,84,179],"dataset":[71],"shortest":[74],"paths":[75,136],"as":[76,195,197],"target":[77,119],"input.":[78],"While":[79],"this":[80],"quite":[82],"effective":[83],"many":[85],"problems,":[86,184],"we":[87],"show":[88],"it":[89],"can":[90],"fail":[91],"face":[94],"complex":[96],"obstacle":[97],"configurations":[98],"or":[99],"mismatch":[100],"between":[101],"training":[102,115],"and":[103,169,189],"testing.":[104],"present":[106],"an":[107],"algorithm":[108],"LEGO":[109,178],"addresses":[111],"these":[112,127,147,167],"issues":[113],"by":[114],"CVAE":[117],"samples":[120,128,148],"satisfy":[122],"two":[123],"important":[124],"criteria.":[125],"Firstly,":[126],"belong":[129],"only":[130],"bottleneck":[132],"regions":[133,154],"along":[134],"near-optimal":[135],"are":[138,149],"otherwise":[139],"difficult-":[140],"to-sample":[141],"uniform":[144],"sampler.":[145],"Secondly,":[146],"across":[152],"diverse":[153],"maximize":[156],"likelihood":[158],"existing.":[163],"formally":[165],"define":[166],"properties":[168],"prove":[170],"performance":[171],"guarantees":[172],"LEGO.":[174],"extensively":[176],"evaluate":[177],"range":[181],"planning":[183],"including":[185],"robot":[186],"arm":[187],"planning,":[188],"report":[190],"significant":[191],"gains":[192],"over":[193],"heuristics":[194],"well":[196],"learned":[198],"baselines.":[199]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2022-07-19T00:00:00"}