{"id":"https://openalex.org/W1579130168","doi":"https://doi.org/10.1109/icra.2015.7139222","title":"Leveraged non-stationary Gaussian process regression for autonomous robot navigation","display_name":"Leveraged non-stationary Gaussian process regression for autonomous robot navigation","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1579130168","doi":"https://doi.org/10.1109/icra.2015.7139222","mag":"1579130168"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2015.7139222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2015.7139222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Robotics and Automation (ICRA)","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/A5047885515","display_name":"Sungjoon Choi","orcid":"https://orcid.org/0000-0002-3049-8212"},"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":true,"raw_author_name":"Sungjoon Choi","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074532898","display_name":"Eunwoo Kim","orcid":"https://orcid.org/0000-0003-0840-0044"},"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":"Eunwoo Kim","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604922","display_name":"Kyungjae Lee","orcid":"https://orcid.org/0000-0003-0147-2715"},"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":"Kyungjae Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033764106","display_name":"Songhwai Oh","orcid":"https://orcid.org/0000-0002-9781-2018"},"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":"Songhwai Oh","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, 151-744, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047885515"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":2.669,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.91407709,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"473","last_page":"478"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9871000051498413,"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/T11236","display_name":"Control Systems and Identification","score":0.9853000044822693,"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/gaussian-process","display_name":"Gaussian process","score":0.746720016002655},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7128157019615173},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5329039692878723},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5292529463768005},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.510429322719574},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5022706985473633},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.46046707034111023},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.45148569345474243},{"id":"https://openalex.org/keywords/kernel-regression","display_name":"Kernel regression","score":0.4445033073425293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43301868438720703},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3831980526447296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3625642657279968},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3248475193977356},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3053727447986603},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2557578682899475}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.746720016002655},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7128157019615173},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5329039692878723},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5292529463768005},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.510429322719574},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5022706985473633},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.46046707034111023},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.45148569345474243},{"id":"https://openalex.org/C200695384","wikidata":"https://www.wikidata.org/wiki/Q1739319","display_name":"Kernel regression","level":3,"score":0.4445033073425293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43301868438720703},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3831980526447296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3625642657279968},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3248475193977356},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3053727447986603},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2557578682899475},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2015.7139222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2015.7139222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Robotics and Automation (ICRA)","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":16,"referenced_works":["https://openalex.org/W1560724230","https://openalex.org/W1712920919","https://openalex.org/W1746819321","https://openalex.org/W2041263603","https://openalex.org/W2065427145","https://openalex.org/W2153347097","https://openalex.org/W2154032554","https://openalex.org/W2154256781","https://openalex.org/W2187580259","https://openalex.org/W3195149063","https://openalex.org/W4211049957","https://openalex.org/W4298242620","https://openalex.org/W4388290814","https://openalex.org/W6682399247","https://openalex.org/W6686821501","https://openalex.org/W6847750346"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W4293503520","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655","https://openalex.org/W2213164457"],"abstract_inverted_index":{"In":[0,23,112],"this":[1,37,61,113],"paper,":[2],"we":[3,41,98],"propose":[4],"a":[5,19,25,107],"novel":[6],"regression":[7,21,33,69,105],"method":[8],"that":[9,135],"can":[10,42,70],"incorporate":[11],"both":[12,50,139],"positive":[13,51,76,87,116,140,148],"and":[14,52,123,141],"negative":[15,53,81,125,142],"training":[16,158],"data":[17,77,117,126,143,149],"into":[18],"single":[20],"framework.":[22],"detail,":[24],"leveraged":[26,65,91,101],"kernel":[27,39,92],"function":[28,93],"for":[29],"non-stationary":[30,66,102],"Gaussian":[31,67,103],"process":[32,68,104],"is":[34],"proposed.":[35],"With":[36],"new":[38],"function,":[40],"vary":[43],"the":[44,63,72,75,80,86,90,100,115,124,136,145,154,161],"correlation":[45],"betwen":[46],"two":[47],"inputs":[48],"in":[49,151],"directions":[54],"by":[55],"adjusting":[56],"leverage":[57],"parameters.":[58],"By":[59],"using":[60,94,138,147],"property,":[62],"resulting":[64],"anchor":[71],"regressor":[73],"to":[74,106,119,121,130],"while":[78],"avoiding":[79],"data.":[82],"We":[83],"first":[84],"prove":[85],"semi-definiteness":[88],"of":[89,153,160],"Bochner's":[95],"theorem.":[96],"Then,":[97],"apply":[99],"real-time":[108],"motion":[109],"control":[110],"problem.":[111],"case,":[114],"refer":[118],"what":[120,128],"do":[122],"indicate":[127],"not":[129],"do.":[131],"The":[132],"results":[133],"show":[134],"controller":[137,146],"outperforms":[144],"only":[150],"terms":[152],"collision":[155],"rate":[156],"given":[157],"sets":[159],"same":[162],"size.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
