{"id":"https://openalex.org/W1784596654","doi":"https://doi.org/10.1109/ivs.2015.7225670","title":"Sampling recovery for closed loop rapidly expanding random tree using brake profile regeneration","display_name":"Sampling recovery for closed loop rapidly expanding random tree using brake profile regeneration","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1784596654","doi":"https://doi.org/10.1109/ivs.2015.7225670","mag":"1784596654"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2015.7225670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2015.7225670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Intelligent Vehicles Symposium (IV)","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/A5056079522","display_name":"Niclas Evestedt","orcid":"https://orcid.org/0000-0003-2131-4589"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Niclas Evestedt","raw_affiliation_strings":["Division of Automatic Control, Link\u00f6ping University, Sweden","Division of Automatic Control, Linkoping University, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Division of Automatic Control, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Division of Automatic Control, Linkoping University, Sweden#TAB#","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028497393","display_name":"Daniel Axehill","orcid":"https://orcid.org/0000-0001-6957-2603"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Daniel Axehill","raw_affiliation_strings":["Division of Automatic Control, Link\u00f6ping University, Sweden","Division of Automatic Control, Linkoping University, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Division of Automatic Control, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Division of Automatic Control, Linkoping University, Sweden#TAB#","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018922157","display_name":"Marco Trincavelli","orcid":"https://orcid.org/0000-0003-0195-2102"},"institutions":[{"id":"https://openalex.org/I1294350288","display_name":"Scania (Sweden)","ror":"https://ror.org/03g4sde39","country_code":"SE","type":"company","lineage":["https://openalex.org/I1294350288"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Marco Trincavelli","raw_affiliation_strings":["Research and Development, Scania CV AB, S\u00f6dert\u00e4lje, Sweden","Research and Development, Scania CV AB, 151 87 S\u00f6dert\u00e4lje, Sweden"],"affiliations":[{"raw_affiliation_string":"Research and Development, Scania CV AB, S\u00f6dert\u00e4lje, Sweden","institution_ids":["https://openalex.org/I1294350288"]},{"raw_affiliation_string":"Research and Development, Scania CV AB, 151 87 S\u00f6dert\u00e4lje, Sweden","institution_ids":["https://openalex.org/I1294350288"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058002446","display_name":"Fredrik Gustafsson","orcid":"https://orcid.org/0000-0003-3270-171X"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Gustafsson","raw_affiliation_strings":["Division of Automatic Control, Link\u00f6ping University, Sweden","Division of Automatic Control, Linkoping University, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Division of Automatic Control, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Division of Automatic Control, Linkoping University, Sweden#TAB#","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056079522"],"corresponding_institution_ids":["https://openalex.org/I102134673"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.55996449,"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":"101","last_page":"106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998999834060669,"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":0.9998999834060669,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/random-tree","display_name":"Random tree","score":0.727914035320282},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6786664724349976},{"id":"https://openalex.org/keywords/brake","display_name":"Brake","score":0.6585206389427185},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6170651912689209},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.614937424659729},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5784226059913635},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.561065673828125},{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.5437941551208496},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4623379111289978},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.44319796562194824},{"id":"https://openalex.org/keywords/simple-random-sample","display_name":"Simple random sample","score":0.42971518635749817},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4260149300098419},{"id":"https://openalex.org/keywords/sampling-scheme","display_name":"Sampling scheme","score":0.41678112745285034},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4167572557926178},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.36655232310295105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1907566785812378},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.156760573387146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15493881702423096},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.13681593537330627},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.10333538055419922},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.0906018614768982}],"concepts":[{"id":"https://openalex.org/C2776839635","wikidata":"https://www.wikidata.org/wiki/Q14942679","display_name":"Random tree","level":4,"score":0.727914035320282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6786664724349976},{"id":"https://openalex.org/C2780999251","wikidata":"https://www.wikidata.org/wiki/Q17022503","display_name":"Brake","level":2,"score":0.6585206389427185},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6170651912689209},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.614937424659729},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5784226059913635},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.561065673828125},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.5437941551208496},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4623379111289978},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.44319796562194824},{"id":"https://openalex.org/C20353970","wikidata":"https://www.wikidata.org/wiki/Q1056998","display_name":"Simple random sample","level":3,"score":0.42971518635749817},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4260149300098419},{"id":"https://openalex.org/C2985139394","wikidata":"https://www.wikidata.org/wiki/Q49908","display_name":"Sampling scheme","level":3,"score":0.41678112745285034},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4167572557926178},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.36655232310295105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1907566785812378},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.156760573387146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15493881702423096},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.13681593537330627},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.10333538055419922},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0906018614768982},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"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/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2015.7225670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2015.7225670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1870703471","https://openalex.org/W1983948265","https://openalex.org/W2000359213","https://openalex.org/W2014340571","https://openalex.org/W2055207897","https://openalex.org/W2059596647","https://openalex.org/W2095945798","https://openalex.org/W2113029345","https://openalex.org/W2154256781","https://openalex.org/W2165216595","https://openalex.org/W2313274380","https://openalex.org/W2326206646","https://openalex.org/W4230028510","https://openalex.org/W4248106410","https://openalex.org/W4293682399","https://openalex.org/W6646284570"],"related_works":["https://openalex.org/W1991478428","https://openalex.org/W3158818664","https://openalex.org/W2372633663","https://openalex.org/W2863424594","https://openalex.org/W2564325388","https://openalex.org/W2108906364","https://openalex.org/W2371294653","https://openalex.org/W1660309994","https://openalex.org/W2118356379","https://openalex.org/W2160082631"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"an":[3],"extension":[4],"to":[5,25,106],"the":[6,27,55,80,86,94,104,114,130],"sampling":[7,66],"based":[8],"motion":[9],"planning":[10],"framework":[11,16,56,105],"CL-RRT":[12],"is":[13],"presented.":[14],"The":[15],"uses":[17],"a":[18,22,32,51,65,71,107,117],"system":[19,43],"model":[20],"and":[21,30,45,91,112,123],"stabilizing":[23],"controller":[24],"sample":[26],"perceived":[28],"environment":[29],"build":[31],"tree":[33],"of":[34,88,96,132],"possible":[35],"trajectories":[36,90],"that":[37,69,98,125],"are":[38,47],"evaluated":[39],"for":[40,136],"execution.":[41,137],"Complex":[42],"models":[44],"constraints":[46],"easily":[48],"handled":[49],"by":[50],"forward":[52,81],"simulation":[53],"making":[54],"widely":[57],"applicable.":[58],"To":[59],"increase":[60],"operational":[61],"safety":[62],"we":[63],"propose":[64],"recovery":[67],"scheme":[68],"performs":[70],"deterministic":[72],"brake":[73],"profile":[74],"regeneration":[75],"using":[76],"collision":[77],"information":[78],"from":[79],"simulation.":[82],"This":[83],"greatly":[84,128],"increases":[85,129],"number":[87,95,131],"safe":[89],"also":[92],"reduces":[93],"samples":[97],"produce":[99],"infeasible":[100],"results.":[101],"We":[102],"apply":[103],"Scania":[108],"G480":[109],"mining":[110],"truck":[111],"evaluate":[113],"algorithm":[115],"in":[116],"simple":[118],"yet":[119],"challenging":[120],"obstacle":[121],"course":[122],"show":[124],"our":[126],"approach":[127],"feasible":[133],"paths":[134],"available":[135]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
