{"id":"https://openalex.org/W2139630381","doi":"https://doi.org/10.1109/iros.2010.5650949","title":"Robot Learning by Demonstration with local Gaussian process regression","display_name":"Robot Learning by Demonstration with local Gaussian process regression","publication_year":2010,"publication_date":"2010-10-01","ids":{"openalex":"https://openalex.org/W2139630381","doi":"https://doi.org/10.1109/iros.2010.5650949","mag":"2139630381"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2010.5650949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2010.5650949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE/RSJ International Conference on Intelligent Robots and Systems","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/A5052220109","display_name":"Matti Schneider","orcid":"https://orcid.org/0000-0001-7017-3618"},"institutions":[{"id":"https://openalex.org/I4210126364","display_name":"University of Education Weingarten","ror":"https://ror.org/031eq5e98","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210126364"]},{"id":"https://openalex.org/I24227732","display_name":"University of Applied Sciences Ravensburg-Weingarten","ror":"https://ror.org/00s4rmz74","country_code":"DE","type":"education","lineage":["https://openalex.org/I24227732"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"M Schneider","raw_affiliation_strings":["University of Applied Sciences, Weingarten, Germany","University of Applied Sciences, Ravensburg\u2010Weingarten, Germany"],"affiliations":[{"raw_affiliation_string":"University of Applied Sciences, Weingarten, Germany","institution_ids":["https://openalex.org/I4210126364"]},{"raw_affiliation_string":"University of Applied Sciences, Ravensburg\u2010Weingarten, Germany","institution_ids":["https://openalex.org/I24227732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016544515","display_name":"Wolfgang Ertel","orcid":"https://orcid.org/0009-0005-8967-3766"},"institutions":[{"id":"https://openalex.org/I4210126364","display_name":"University of Education Weingarten","ror":"https://ror.org/031eq5e98","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210126364"]},{"id":"https://openalex.org/I24227732","display_name":"University of Applied Sciences Ravensburg-Weingarten","ror":"https://ror.org/00s4rmz74","country_code":"DE","type":"education","lineage":["https://openalex.org/I24227732"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"W Ertel","raw_affiliation_strings":["University of Applied Sciences, Weingarten, Germany","University of Applied Sciences, Ravensburg\u2010Weingarten, Germany"],"affiliations":[{"raw_affiliation_string":"University of Applied Sciences, Weingarten, Germany","institution_ids":["https://openalex.org/I4210126364"]},{"raw_affiliation_string":"University of Applied Sciences, Ravensburg\u2010Weingarten, Germany","institution_ids":["https://openalex.org/I24227732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052220109"],"corresponding_institution_ids":["https://openalex.org/I24227732","https://openalex.org/I4210126364"],"apc_list":null,"apc_paid":null,"fwci":7.2167,"has_fulltext":false,"cited_by_count":109,"citation_normalized_percentile":{"value":0.97034819,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"255","last_page":"260"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9172999858856201,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.7211941480636597},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.686342716217041},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6755254864692688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6693487763404846},{"id":"https://openalex.org/keywords/programming-by-demonstration","display_name":"Programming by demonstration","score":0.6587091684341431},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5959709882736206},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.555610179901123},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5359758734703064},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5252712965011597},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4950813353061676},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.48062723875045776},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4292408227920532},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3432867228984833},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1286797821521759}],"concepts":[{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.7211941480636597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.686342716217041},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6755254864692688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6693487763404846},{"id":"https://openalex.org/C2779038628","wikidata":"https://www.wikidata.org/wiki/Q7248497","display_name":"Programming by demonstration","level":3,"score":0.6587091684341431},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5959709882736206},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.555610179901123},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5359758734703064},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5252712965011597},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4950813353061676},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.48062723875045776},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4292408227920532},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3432867228984833},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1286797821521759},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2010.5650949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2010.5650949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE/RSJ International Conference on Intelligent Robots and Systems","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":27,"referenced_works":["https://openalex.org/W130216483","https://openalex.org/W1560270123","https://openalex.org/W1571870753","https://openalex.org/W1580216809","https://openalex.org/W1746819321","https://openalex.org/W1986014385","https://openalex.org/W2098949458","https://openalex.org/W2099768828","https://openalex.org/W2102341081","https://openalex.org/W2117778675","https://openalex.org/W2119388568","https://openalex.org/W2123967136","https://openalex.org/W2128677288","https://openalex.org/W2129564505","https://openalex.org/W2149764047","https://openalex.org/W2158607953","https://openalex.org/W2170078560","https://openalex.org/W2406715912","https://openalex.org/W2545129501","https://openalex.org/W3029645440","https://openalex.org/W4211049957","https://openalex.org/W4293775970","https://openalex.org/W6634689341","https://openalex.org/W6674660115","https://openalex.org/W6674989108","https://openalex.org/W6678157427","https://openalex.org/W6684632043"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655","https://openalex.org/W2139630381"],"abstract_inverted_index":{"In":[0,63,106],"recent":[1],"years":[2],"there":[3],"was":[4],"a":[5,33,43,81,86,133],"tremendous":[6],"progress":[7],"in":[8,25,104],"robotic":[9],"systems,":[10],"and":[11,23,53,72],"however":[12],"also":[13],"increased":[14],"expectations:":[15],"A":[16],"robot":[17,135],"should":[18],"be":[19,55,77],"easy":[20],"to":[21,37,49,79,101],"program":[22],"reliable":[24],"task":[26],"execution.":[27],"Learning":[28,118],"from":[29],"Demonstration":[30,120],"(LfD)":[31],"offers":[32],"very":[34,44],"promising":[35],"alternative":[36],"classical":[38],"engineering":[39],"approaches.":[40],"LfD":[41],"is":[42],"natural":[45],"way":[46],"for":[47],"humans":[48],"interact":[50],"with":[51],"robots":[52],"will":[54],"an":[56,130],"essential":[57],"part":[58],"of":[59,122],"future":[60],"service":[61],"robots.":[62],"this":[64],"work":[65,103],"we":[66,110,128],"first":[67],"review":[68],"heteroscedastic":[69],"Gaussian":[70,88],"processes":[71],"show":[73,111],"how":[74,112,139],"these":[75,113,141],"can":[76],"used":[78],"encode":[80],"task.":[82],"We":[83],"then":[84],"introduce":[85],"new":[87],"process":[89],"regression":[90],"model":[91],"that":[92,137],"clusters":[93],"the":[94,102,107,117,126],"input":[95],"space":[96],"into":[97,116],"smaller":[98],"subsets":[99],"similar":[100],"[11].":[105],"next":[108],"step":[109],"approaches":[114,142],"fit":[115],"by":[119],"framework":[121],"[2],":[123],"[3].":[124],"At":[125],"end":[127],"present":[129],"experiment":[131],"on":[132],"real":[134],"arm":[136],"shows":[138],"all":[140],"interact.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
