{"id":"https://openalex.org/W2029846889","doi":"https://doi.org/10.1109/icra.2014.6907208","title":"General probabilistic bounds for trajectories using only mean and variance","display_name":"General probabilistic bounds for trajectories using only mean and variance","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2029846889","doi":"https://doi.org/10.1109/icra.2014.6907208","mag":"2029846889"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2014.6907208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2014.6907208","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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/A5101415794","display_name":"Cheng Fang","orcid":"https://orcid.org/0000-0003-4318-1078"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cheng Fang","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory Massachusetts, Institute of Technology, Cambridge, MA, USA","#N#Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St., Cambridge, MA 02139, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory Massachusetts, Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"#N#Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St., Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101709620","display_name":"Brian Williams","orcid":"https://orcid.org/0000-0002-1057-3940"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian C. Williams","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory Massachusetts, Institute of Technology, Cambridge, MA, USA","#N#Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St., Cambridge, MA 02139, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory Massachusetts, Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"#N#Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St., Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"46","issue":null,"first_page":"2501","last_page":"2506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10142","display_name":"Formal Methods in Verification","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10142","display_name":"Formal Methods in Verification","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.991599977016449,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9907000064849854,"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":0.5750625729560852},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5717999935150146},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.5224353671073914},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5000803470611572},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4737815856933594},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4589231610298157},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4387664198875427},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.41558638215065},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.41483980417251587},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3089885115623474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26796022057533264},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.2221069037914276},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1546034812927246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5750625729560852},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5717999935150146},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5224353671073914},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5000803470611572},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4737815856933594},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4589231610298157},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4387664198875427},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.41558638215065},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.41483980417251587},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3089885115623474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26796022057533264},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2221069037914276},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1546034812927246},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2014.6907208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2014.6907208","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W128192963","https://openalex.org/W1424654272","https://openalex.org/W1981367618","https://openalex.org/W2066778083","https://openalex.org/W2067778155","https://openalex.org/W2104241562","https://openalex.org/W2123487311","https://openalex.org/W2128582898","https://openalex.org/W2139809908","https://openalex.org/W2143964432","https://openalex.org/W2160337655","https://openalex.org/W2168359464","https://openalex.org/W2207944422","https://openalex.org/W4214717370","https://openalex.org/W4232753567","https://openalex.org/W6679273940"],"related_works":["https://openalex.org/W4290792893","https://openalex.org/W2224648581","https://openalex.org/W2136053165","https://openalex.org/W2042726902","https://openalex.org/W2018828049","https://openalex.org/W1598979804","https://openalex.org/W3102909640","https://openalex.org/W2046712581","https://openalex.org/W2908970796","https://openalex.org/W2100031985"],"abstract_inverted_index":{"Two":[0],"ideas":[1],"have":[2],"gained":[3],"traction":[4],"in":[5,7,53],"research":[6],"the":[8,24,55,64,89,92,108,112,129,133,138,142,154,170,175,196,225,228,241,244,249],"robotics":[9],"planning":[10,13],"community.":[11],"Activity":[12],"has":[14,41],"become":[15],"popular":[16],"where":[17],"a":[18,46,201,210],"library":[19],"of":[20,23,48,57,63,71,91,101,141,174,227],"predefined":[21],"manipulation":[22],"vehicle":[25,113],"state":[26],"is":[27,30,59,178,190,209],"accessible,":[28],"and":[29,122,215,247],"commonly":[31],"used":[32],"for":[33,68,111,132,186,220,235],"missions":[34],"with":[35,243],"complex":[36,72],"goal":[37],"specifications.":[38],"Another":[39],"focus":[40],"been":[42],"chance-constrained":[43,77],"programming":[44],"as":[45,120,200],"method":[47],"providing":[49],"robust":[50,69],"motion":[51],"planning,":[52,79],"which":[54],"probability":[56],"failure":[58],"bounded.":[60],"A":[61],"combination":[62],"two":[65,156,172],"would":[66,104],"allow":[67],"satisfaction":[70],"directives.":[73],"However,":[74],"to":[75,84,117,127],"perform":[76],"activity":[78],"we":[80,103,124,163,204,238],"must":[81],"be":[82,97,147],"able":[83],"provide":[85],"probabilistic":[86],"bounds":[87,219],"on":[88],"trajectory":[90],"vehicle.":[93],"While":[94],"this":[95,161],"may":[96,145,239],"done":[98],"through":[99,158],"propagation":[100,167,189,242],"statistics,":[102],"require":[105],"information":[106],"about":[107],"actuation":[109,143,176],"noise":[110,144],"dynamics.":[114],"In":[115,135,160],"addition":[116],"such":[118],"parameters":[119],"mean":[121,223],"variance,":[123],"also":[125],"need":[126],"know":[128],"appropriate":[130],"function":[131],"noise.":[134,182],"many":[136],"cases,":[137],"exact":[139],"distribution":[140],"not":[146],"known,":[148,179],"although":[149],"researchers":[150],"can":[151,205],"easily":[152],"approximate":[153,240],"first":[155,171],"moments":[157,173],"calibrations.":[159],"work":[162],"look":[164],"at":[165,195],"statistics":[166],"when":[168],"only":[169],"uncertainty":[177],"assuming":[180],"white":[181],"We":[183,231],"show":[184,206,233],"that":[185,207],"linear":[187],"systems,":[188],"exact.":[191],"Further,":[192],"by":[193],"looking":[194],"expected":[197],"error":[198,218],"squared":[199],"stochastic":[202],"process,":[203],"it":[208],"submartingale":[211],"under":[212],"certain":[213],"assumptions,":[214],"thus":[216],"derive":[217],"deviation":[221],"from":[222],"over":[224],"duration":[226],"entire":[229],"path.":[230],"empirically":[232],"that,":[234],"nonlinear":[236],"dynamics,":[237],"unscented":[245],"transform,":[246],"obtain":[248],"corresponding":[250],"bounds.":[251]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
