{"id":"https://openalex.org/W3093169645","doi":"https://doi.org/10.1109/lra.2021.3057055","title":"Robot Learning With Crash Constraints","display_name":"Robot Learning With Crash Constraints","publication_year":2021,"publication_date":"2021-02-03","ids":{"openalex":"https://openalex.org/W3093169645","doi":"https://doi.org/10.1109/lra.2021.3057055","mag":"3093169645"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2021.3057055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3057055","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2010.08669","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Alonso Marco","orcid":"https://orcid.org/0000-0002-5764-6713"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alonso Marco","raw_affiliation_strings":["Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Dominik Baumann","orcid":"https://orcid.org/0000-0001-7340-2180"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]},{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Baumann","raw_affiliation_strings":["Institute for Data Science in Mechanical Engineering, RWTH Aachen University, Aachen, Germany","Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Data Science in Mechanical Engineering, RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Majid Khadiv","orcid":"https://orcid.org/0000-0001-9889-6543"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Majid Khadiv","raw_affiliation_strings":["Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Philipp Hennig","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]},{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Philipp Hennig","raw_affiliation_strings":["Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Germany","University of T\u00fcbingen, Computer Science Department, T\u00fcbingen, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Germany","institution_ids":["https://openalex.org/I4210135521"]},{"raw_affiliation_string":"University of T\u00fcbingen, Computer Science Department, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ludovic Righetti","orcid":"https://orcid.org/0000-0002-6458-9112"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]},{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Ludovic Righetti","raw_affiliation_strings":["Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany","New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I4210135521"]},{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sebastian Trimpe","orcid":"https://orcid.org/0000-0002-2785-2487"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]},{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Trimpe","raw_affiliation_strings":["Institute for Data Science in Mechanical Engineering, RWTH Aachen University, Aachen, Germany","Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Data Science in Mechanical Engineering, RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems, T\u00fcbingen/Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I4210135521"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210135521"],"apc_list":null,"apc_paid":null,"fwci":2.3797,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.90221837,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"6","issue":"2","first_page":"1439","last_page":"1446"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.421099990606308,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.421099990606308,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.38999998569488525,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.04019999876618385,"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/constraint","display_name":"Constraint (computer-aided design)","score":0.7379000186920166},{"id":"https://openalex.org/keywords/crash","display_name":"Crash","score":0.6538000106811523},{"id":"https://openalex.org/keywords/constraint-learning","display_name":"Constraint learning","score":0.5414000153541565},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4124999940395355},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3977000117301941},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.37929999828338623}],"concepts":[{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.7379000186920166},{"id":"https://openalex.org/C183469790","wikidata":"https://www.wikidata.org/wiki/Q333501","display_name":"Crash","level":2,"score":0.6538000106811523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6118999719619751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5740000009536743},{"id":"https://openalex.org/C29230964","wikidata":"https://www.wikidata.org/wiki/Q5164376","display_name":"Constraint learning","level":5,"score":0.5414000153541565},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5227000117301941},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3977000117301941},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C173404611","wikidata":"https://www.wikidata.org/wiki/Q528588","display_name":"Constraint programming","level":3,"score":0.2939000129699707},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C2775907273","wikidata":"https://www.wikidata.org/wiki/Q7805281","display_name":"Time constraint","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.25519999861717224}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lra.2021.3057055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3057055","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2010.08669","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.08669","pdf_url":"https://arxiv.org/pdf/2010.08669","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2010.08669","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.08669","pdf_url":"https://arxiv.org/pdf/2010.08669","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W770013183","https://openalex.org/W1588959569","https://openalex.org/W1887094882","https://openalex.org/W2021207328","https://openalex.org/W2119401655","https://openalex.org/W2124060711","https://openalex.org/W2143277772","https://openalex.org/W2171072927","https://openalex.org/W2186013251","https://openalex.org/W2192203593","https://openalex.org/W2346505884","https://openalex.org/W2539084569","https://openalex.org/W2737488931","https://openalex.org/W2772449134","https://openalex.org/W2915553973","https://openalex.org/W2963647792","https://openalex.org/W2977389550","https://openalex.org/W2990956201","https://openalex.org/W3011771794","https://openalex.org/W6633611819","https://openalex.org/W6637653338","https://openalex.org/W6683442033","https://openalex.org/W6734090873","https://openalex.org/W6740824378","https://openalex.org/W6743990045","https://openalex.org/W6763801715","https://openalex.org/W6764729444","https://openalex.org/W6773682126","https://openalex.org/W6790668762"],"related_works":[],"abstract_inverted_index":{"In":[0,85],"the":[1,30,60,67,76,108,135,151,166,185,199],"past":[2],"decade,":[3],"numerous":[4],"machine":[5],"learning":[6,31,111],"algorithms":[7,46],"have":[8],"been":[9],"shown":[10],"to":[11,16,25,82],"successfully":[12],"learn":[13],"optimal":[14],"policies":[15],"control":[17],"real":[18,162,186],"robotic":[19],"systems.":[20],"However,":[21],"it":[22],"is":[23,40,55,118,126,169,175],"common":[24],"encounter":[26],"failing":[27,39,98],"behaviors":[28,99],"as":[29,100],"loop":[32],"progresses.":[33],"Specifically,":[34],"in":[35],"robot":[36],"applications":[37],"where":[38,115,165],"undesired":[41],"but":[42],"not":[43],"catastrophic,":[44],"many":[45],"struggle":[47],"with":[48,112,142],"leveraging":[49],"data":[50,69,117,174],"obtained":[51,119,146],"from":[52],"failures.":[53,84],"This":[54],"usually":[56],"caused":[57],"by":[58,128,177],"(i)":[59],"failed":[61],"experiment":[62],"ending":[63],"prematurely,":[64],"or":[65,72],"(ii)":[66],"acquired":[68],"being":[70],"scarce":[71],"corrupted.":[73],"Both":[74],"complicate":[75],"design":[77],"of":[78,110,153,179],"proper":[79],"reward":[80],"functions":[81],"penalize":[83],"this":[86],"letter,":[87],"we":[88],"propose":[89],"a":[90,104,129,161,171],"framework":[91,155],"that":[92,102,137],"addresses":[93],"those":[94,101],"issues.":[95],"We":[96,149],"consider":[97],"violate":[103],"constraint":[105,121,136,167,200],"and":[106,159,193],"address":[107],"problem":[109],"crash":[113],"constraints,":[114],"no":[116],"upon":[120,147],"violation.":[122],"The":[123],"no-data":[124],"case":[125],"addressed":[127],"novel":[130],"GP":[131],"model":[132],"(GPCR)":[133],"for":[134],"combines":[138],"discrete":[139],"events":[140],"(failure/success)":[141],"continuous":[143],"observations":[144],"(only":[145],"success).":[148],"demonstrate":[150],"effectiveness":[152],"our":[154],"on":[156,160,184,197],"simulated":[157],"benchmarks":[158],"jumping":[163],"quadruped,":[164],"threshold":[168],"unknown":[170],"priori.":[172],"Experimental":[173],"collected,":[176],"means":[178],"constrained":[180],"Bayesian":[181],"optimization,":[182],"directly":[183],"robot.":[187],"Our":[188],"results":[189],"outperform":[190],"manual":[191],"tuning":[192],"GPCR":[194],"proves":[195],"useful":[196],"estimating":[198],"threshold.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2020-10-22T00:00:00"}