{"id":"https://openalex.org/W2563186568","doi":"https://doi.org/10.1109/iros.2016.7759551","title":"Pareto-optimal search over configuration space beliefs for anytime motion planning","display_name":"Pareto-optimal search over configuration space beliefs for anytime motion planning","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2563186568","doi":"https://doi.org/10.1109/iros.2016.7759551","mag":"2563186568"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2016.7759551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 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/A5000095866","display_name":"Shushman Choudhury","orcid":"https://orcid.org/0000-0003-4829-8806"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shushman Choudhury","raw_affiliation_strings":["Carnegie Mellon Robotics Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon Robotics Institute","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031390088","display_name":"Christopher M. Dellin","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher M. Dellin","raw_affiliation_strings":["Carnegie Mellon Robotics Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon Robotics Institute","institution_ids":["https://openalex.org/I74973139"]}]},{"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/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siddhartha S. Srinivasa","raw_affiliation_strings":["Carnegie Mellon Robotics Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon Robotics Institute","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0282,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.91472486,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"1","issue":null,"first_page":"3742","last_page":"3749"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":1.0,"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":1.0,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10653","display_name":"Robot Manipulation and Learning","score":0.984000027179718,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.800155758857727},{"id":"https://openalex.org/keywords/probabilistic-roadmap","display_name":"Probabilistic roadmap","score":0.7695487141609192},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.6606993675231934},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.6470369100570679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6198962926864624},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.6034576892852783},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5721660852432251},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5716264843940735},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5152350068092346},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5082833170890808},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.44943156838417053},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.4352743327617645},{"id":"https://openalex.org/keywords/path-length","display_name":"Path length","score":0.43497127294540405},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40633413195610046},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.2849265933036804},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24179524183273315},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21634608507156372}],"concepts":[{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.800155758857727},{"id":"https://openalex.org/C2778803389","wikidata":"https://www.wikidata.org/wiki/Q7246866","display_name":"Probabilistic roadmap","level":4,"score":0.7695487141609192},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.6606993675231934},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.6470369100570679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6198962926864624},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.6034576892852783},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5721660852432251},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5716264843940735},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5152350068092346},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5082833170890808},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.44943156838417053},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.4352743327617645},{"id":"https://openalex.org/C129045301","wikidata":"https://www.wikidata.org/wiki/Q7144654","display_name":"Path length","level":2,"score":0.43497127294540405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40633413195610046},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2849265933036804},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24179524183273315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21634608507156372},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2016.7759551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W119169328","https://openalex.org/W178999881","https://openalex.org/W181534116","https://openalex.org/W1583541992","https://openalex.org/W1964443412","https://openalex.org/W1969483458","https://openalex.org/W1971672424","https://openalex.org/W2000359213","https://openalex.org/W2037034267","https://openalex.org/W2045422729","https://openalex.org/W2071852134","https://openalex.org/W2103524001","https://openalex.org/W2110762409","https://openalex.org/W2112765698","https://openalex.org/W2113222527","https://openalex.org/W2114628632","https://openalex.org/W2128353551","https://openalex.org/W2128990851","https://openalex.org/W2136354320","https://openalex.org/W2141664020","https://openalex.org/W2151184669","https://openalex.org/W2159722616","https://openalex.org/W2169528473","https://openalex.org/W2408262133","https://openalex.org/W2763506955","https://openalex.org/W3099020824","https://openalex.org/W3103346840","https://openalex.org/W6785809450","https://openalex.org/W7019850852"],"related_works":["https://openalex.org/W2107702345","https://openalex.org/W2137520303","https://openalex.org/W1536392978","https://openalex.org/W2216928063","https://openalex.org/W4381746183","https://openalex.org/W2389713625","https://openalex.org/W4308217561","https://openalex.org/W2134348961","https://openalex.org/W2115192598","https://openalex.org/W2116162693"],"abstract_inverted_index":{"We":[0,54,96,147],"present":[1],"POMP":[2,173],"(Pareto":[3],"Optimal":[4],"Motion":[5],"Planner),":[6],"an":[7],"anytime":[8,188],"algorithm":[9],"for":[10,43,115,180,187],"geometric":[11],"path":[12,48,160],"planning":[13,31,198],"on":[14],"roadmaps.":[15],"For":[16],"robots":[17],"with":[18,162,176],"several":[19],"degrees":[20],"of":[21,40,91,124,165,193],"freedom,":[22],"collision":[23,41,77,145,194],"checks":[24,42,104,195],"are":[25,62,105],"computationally":[26],"expensive":[27],"and":[28,49,178,185,196],"often":[29],"dominate":[30],"time.":[32,199],"Our":[33,130,169],"goal":[34],"is":[35,119,132,153],"to":[36,73,82,121,133,156],"minimize":[37],"the":[38,45,57,75,89,98,122,125,158,181],"number":[39],"obtaining":[44],"first":[46,182],"feasible":[47,52,183],"successively":[50],"shorter":[51],"paths.":[53],"assume":[55],"that":[56,87,118,150,172],"roadmaps":[58],"we":[59],"search":[60],"over":[61,100,144],"embedded":[63],"in":[64,128,167,191],"a":[65,84,112,163],"continuous":[66],"ambient":[67],"space,":[68],"where":[69],"nearby":[70],"points":[71],"tend":[72],"share":[74],"same":[76],"state.":[78],"This":[79,107],"enables":[80],"us":[81,110],"formulate":[83],"probabilistic":[85],"model":[86,99,108],"computes":[88],"probability":[90,123],"unevaluated":[92],"configurations":[93],"being":[94,127,166],"collision-free.":[95],"update":[97],"time":[101],"as":[102],"more":[103],"performed.":[106],"lets":[109],"define":[111],"weighting":[113],"function":[114],"roadmap":[116],"edges":[117],"related":[120],"edge":[126,142],"collision.":[129,168],"approach":[131],"trade":[134],"off":[135],"between":[136],"these":[137],"two":[138],"weights,":[139],"gradually":[140],"prioritizing":[141],"length":[143],"likelihood.":[146],"also":[148],"show":[149],"this":[151],"tradeoff":[152],"approximately":[154],"equivalent":[155],"minimizing":[157],"expected":[159],"length,":[161],"penalty":[164],"experiments":[170],"demonstrate":[171],"performs":[174],"comparably":[175],"RRTConnect":[177],"LazyPRM":[179],"path,":[184],"BIT*":[186],"performance,":[189],"both":[190],"terms":[192],"total":[197]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
