{"id":"https://openalex.org/W7123346062","doi":"https://doi.org/10.1109/cdc57313.2025.11312645","title":"Egocentric Conformal Prediction for Safe and Efficient Navigation in Dynamic Cluttered Environments","display_name":"Egocentric Conformal Prediction for Safe and Efficient Navigation in Dynamic Cluttered Environments","publication_year":2025,"publication_date":"2025-12-09","ids":{"openalex":"https://openalex.org/W7123346062","doi":"https://doi.org/10.1109/cdc57313.2025.11312645"},"language":null,"primary_location":{"id":"doi:10.1109/cdc57313.2025.11312645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc57313.2025.11312645","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 64th Conference on Decision and Control (CDC)","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/A5026749569","display_name":"Shin Js","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeuk Shin","raw_affiliation_strings":["Seoul National University,ASRI,Department of Electrical and Computer Engineering,Seoul,South Korea,08826"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,ASRI,Department of Electrical and Computer Engineering,Seoul,South Korea,08826","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018247634","display_name":"Jungjin Lee","orcid":"https://orcid.org/0000-0003-2174-6365"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jungjin Lee","raw_affiliation_strings":["Seoul National University,ASRI,Department of Electrical and Computer Engineering,Seoul,South Korea,08826"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,ASRI,Department of Electrical and Computer Engineering,Seoul,South Korea,08826","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122853956","display_name":"Insoon Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Insoon Yang","raw_affiliation_strings":["Seoul National University,ASRI,Department of Electrical and Computer Engineering,Seoul,South Korea,08826"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,ASRI,Department of Electrical and Computer Engineering,Seoul,South Korea,08826","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4985,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72339621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4910","last_page":"4917"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.7728000283241272,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.7728000283241272,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.06350000202655792,"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":0.027699999511241913,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5195000171661377},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4438000023365021},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.430400013923645},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.41670000553131104},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.4032999873161316},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.3921999931335449},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.3815999925136566},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.36739999055862427}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6868000030517578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6740000247955322},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4438000023365021},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44350001215934753},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.4032999873161316},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3921999931335449},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.3815999925136566},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3797999918460846},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.2687999904155731},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.259799987077713},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc57313.2025.11312645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc57313.2025.11312645","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 64th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1553101044","https://openalex.org/W1970206276","https://openalex.org/W2532516272","https://openalex.org/W3116651890","https://openalex.org/W3127710918","https://openalex.org/W4287186233","https://openalex.org/W4383108443","https://openalex.org/W4383112515","https://openalex.org/W4387415302","https://openalex.org/W4391021526","https://openalex.org/W4393146905","https://openalex.org/W4400189275","https://openalex.org/W4401414276","https://openalex.org/W4401415606","https://openalex.org/W4405179398","https://openalex.org/W4414556916","https://openalex.org/W7123346062"],"related_works":[],"abstract_inverted_index":{"Conformal":[0],"prediction":[1,37,45,81],"(CP)":[2],"has":[3],"recently":[4],"emerged":[5],"as":[6,14,164],"a":[7,71,97,110],"powerful":[8],"tool":[9],"in":[10,28,136,154],"robotics":[11],"and":[12],"control,":[13,39],"it":[15],"enables":[16],"distribution-free":[17],"calibration":[18],"of":[19,156],"complex,":[20],"data-driven":[21],"models":[22,41],"with":[23,125],"rigorous":[24],"statistical":[25],"guarantees.":[26],"However,":[27],"robot":[29],"navigation":[30,74],"tasks,":[31],"existing":[32,151],"CP-based":[33,73,152],"methods":[34],"often":[35],"decouple":[36],"from":[38],"evaluating":[40],"without":[42,139],"considering":[43],"whether":[44],"errors":[46],"actually":[47],"compromise":[48],"safety.":[49,123],"Consequently,":[50],"ego-vehicles":[51],"may":[52],"become":[53],"overly":[54],"conservative":[55],"or":[56],"even":[57],"immobilized":[58],"when":[59],"all":[60],"potential":[61],"trajectories":[62],"appear":[63],"infeasible.":[64],"To":[65],"address":[66],"this":[67],"issue,":[68],"we":[69],"propose":[70],"novel":[72],"framework":[75,131],"that":[76,89,147],"responds":[77],"exclusively":[78],"to":[79,96,134,141],"safety-critical":[80],"errors.":[82],"Our":[83],"approach":[84],"introduces":[85],"egocentric":[86],"score":[87,104],"functions":[88,105],"quantify":[90],"how":[91],"much":[92],"closer":[93],"obstacles":[94],"are":[95,106],"candidate":[98,117],"vehicle":[99],"position":[100],"than":[101],"anticipated.":[102],"These":[103],"then":[107],"integrated":[108],"into":[109],"model":[111],"predictive":[112],"control":[113],"scheme,":[114],"wherein":[115],"each":[116],"state":[118],"is":[119],"individually":[120],"evaluated":[121],"for":[122],"Combined":[124],"an":[126],"adaptive":[127],"CP":[128],"mechanism,":[129],"our":[130,148],"dynamically":[132],"adjusts":[133],"changes":[135],"obstacle":[137],"motion":[138],"resorting":[140],"unnecessary":[142],"conservatism.":[143],"Theoretical":[144],"analyses":[145],"indicate":[146],"method":[149],"outperforms":[150],"approaches":[153],"terms":[155],"cost-efficiency":[157],"while":[158],"maintaining":[159],"the":[160],"desired":[161],"safety":[162],"levels,":[163],"further":[165],"validated":[166],"through":[167],"experiments":[168],"on":[169],"real-world":[170],"datasets":[171],"featuring":[172],"densely":[173],"populated":[174],"pedestrian":[175],"environments.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-14T00:00:00"}
