{"id":"https://openalex.org/W2485586407","doi":"https://doi.org/10.1109/iros.2016.7759417","title":"A sensorimotor reinforcement learning framework for physical Human-Robot Interaction","display_name":"A sensorimotor reinforcement learning framework for physical Human-Robot Interaction","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2485586407","doi":"https://doi.org/10.1109/iros.2016.7759417","mag":"2485586407"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2016.7759417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1607.07939","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038342432","display_name":"Ali Ghadirzadeh","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ali Ghadirzadeh","raw_affiliation_strings":["Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089992361","display_name":"Judith B\u00fctepage","orcid":"https://orcid.org/0000-0001-5344-8042"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Judith Butepage","raw_affiliation_strings":["Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054834085","display_name":"Atsuto Maki","orcid":"https://orcid.org/0000-0002-4266-6746"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Atsuto Maki","raw_affiliation_strings":["Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023792180","display_name":"Danica Kragi\u0107","orcid":"https://orcid.org/0000-0003-2965-2953"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Danica Kragic","raw_affiliation_strings":["Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082269387","display_name":"M\u00e5rten Bj\u00f6rkman","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Marten Bjorkman","raw_affiliation_strings":["Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab (CVAP), CSC, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.194,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4664418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2682","last_page":"2688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.989799976348877,"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":0.989799976348877,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9871000051498413,"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/T10879","display_name":"Robotic Locomotion and Control","score":0.9510999917984009,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/action-selection","display_name":"Action selection","score":0.7580429911613464},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.694392740726471},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6604189872741699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6416201591491699},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6268637180328369},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5614010095596313},{"id":"https://openalex.org/keywords/robot-learning","display_name":"Robot learning","score":0.5185442566871643},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5032057166099548},{"id":"https://openalex.org/keywords/human\u2013robot-interaction","display_name":"Human\u2013robot interaction","score":0.4986155033111572},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4959469735622406},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4833042621612549},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.44430530071258545},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4406786859035492},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.35101860761642456},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.31536853313446045},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.29049691557884216},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14752423763275146}],"concepts":[{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.7580429911613464},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.694392740726471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6604189872741699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6416201591491699},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6268637180328369},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5614010095596313},{"id":"https://openalex.org/C188888258","wikidata":"https://www.wikidata.org/wiki/Q7353390","display_name":"Robot learning","level":4,"score":0.5185442566871643},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5032057166099548},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.4986155033111572},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4959469735622406},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4833042621612549},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.44430530071258545},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4406786859035492},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.35101860761642456},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.31536853313446045},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.29049691557884216},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14752423763275146},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iros.2016.7759417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1607.07939","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1607.07939","pdf_url":"https://arxiv.org/pdf/1607.07939","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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"},{"id":"mag:2485586407","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1607.07939","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1607.07939","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1607.07939","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1607.07939","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1607.07939","pdf_url":"https://arxiv.org/pdf/1607.07939","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"display_name":"Partnerships for the goals","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G8657455129","display_name":null,"funder_award_id":"H2020-FETPROACT-2014","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320322581","display_name":"Vetenskapsr\u00e5det","ror":"https://ror.org/03zttf063"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2485586407.pdf","grobid_xml":"https://content.openalex.org/works/W2485586407.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W161356478","https://openalex.org/W1489427801","https://openalex.org/W1966941682","https://openalex.org/W1977655452","https://openalex.org/W1979780394","https://openalex.org/W2011444327","https://openalex.org/W2012587148","https://openalex.org/W2018705428","https://openalex.org/W2024538772","https://openalex.org/W2038973120","https://openalex.org/W2086493383","https://openalex.org/W2088926361","https://openalex.org/W2092544229","https://openalex.org/W2096787288","https://openalex.org/W2107386393","https://openalex.org/W2169187067","https://openalex.org/W2170043047","https://openalex.org/W2192203593","https://openalex.org/W2210018674","https://openalex.org/W2949608212","https://openalex.org/W4205513846","https://openalex.org/W4211089519","https://openalex.org/W6638018090","https://openalex.org/W6675823452"],"related_works":["https://openalex.org/W2791359174","https://openalex.org/W2911965264","https://openalex.org/W12522828","https://openalex.org/W2287257424","https://openalex.org/W2221242619","https://openalex.org/W2824479732","https://openalex.org/W2602598717","https://openalex.org/W3034321388","https://openalex.org/W94382907","https://openalex.org/W3167073030","https://openalex.org/W2271203632","https://openalex.org/W2045824138","https://openalex.org/W2080245757","https://openalex.org/W2990952748","https://openalex.org/W2893178414","https://openalex.org/W2978020414","https://openalex.org/W2565427121","https://openalex.org/W2658779370","https://openalex.org/W1507332434","https://openalex.org/W1503862567"],"abstract_inverted_index":{"Modeling":[0],"of":[1,15,124,130],"physical":[2],"human-robot":[3],"collaborations":[4],"is":[5,61,84],"generally":[6],"a":[7,24,31,39,69,94,98,101,110],"challenging":[8],"problem":[9],"due":[10],"to":[11,33,36,67,93],"the":[12,45,59,80,91,106,122,125,146],"unpredictive":[13],"nature":[14],"human":[16,40,99],"behavior.":[17],"To":[18],"address":[19],"this":[20],"issue,":[21],"we":[22],"present":[23],"data-efficient":[25,133],"reinforcement":[26],"learning":[27],"framework":[28,92],"which":[29,97],"enables":[30],"robot":[32,43,103],"learn":[34],"how":[35],"collaborate":[37],"with":[38],"partner.":[41],"The":[42,56],"learns":[44],"task":[46],"from":[47],"its":[48],"own":[49],"sensorimotor":[50],"experiences":[51],"in":[52,58,96,128],"an":[53,73],"unsupervised":[54],"manner.":[55],"uncertainty":[57,140],"interaction":[60],"modeled":[62],"using":[63],"Gaussian":[64],"processes":[65],"(GP)":[66],"implement":[68],"forward":[70],"model":[71,83,134],"and":[72,100,115,132,141],"action-value":[74],"function.":[75],"Optimal":[76],"action":[77,137],"selection":[78,138],"given":[79],"uncertain":[81],"GP":[82],"ensured":[85],"by":[86],"Bayesian":[87],"optimization.":[88],"We":[89],"apply":[90],"scenario":[95],"PR2":[102],"jointly":[104],"control":[105],"ball":[107],"position":[108],"on":[109,113],"plank":[111],"based":[112],"vision":[114],"force/torque":[116],"data.":[117],"Our":[118],"experimental":[119],"results":[120],"show":[121],"suitability":[123],"proposed":[126],"method":[127],"terms":[129],"fast":[131],"learning,":[135],"optimal":[136],"under":[139],"equal":[142],"role":[143],"sharing":[144],"between":[145],"partners.":[147]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-08T07:41:36.138363","created_date":"2025-10-10T00:00:00"}
