{"id":"https://openalex.org/W3183112146","doi":"https://doi.org/10.1109/iros51168.2021.9635936","title":"Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces","display_name":"Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces","publication_year":2021,"publication_date":"2021-09-27","ids":{"openalex":"https://openalex.org/W3183112146","doi":"https://doi.org/10.1109/iros51168.2021.9635936","mag":"3183112146"},"language":"en","primary_location":{"id":"doi:10.1109/iros51168.2021.9635936","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9635936","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.utwente.nl/en/publications/ab364560-9fd6-47dc-b195-cb424c5d8f51","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001000324","display_name":"Nicol\u00f2 Botteghi","orcid":"https://orcid.org/0000-0003-3676-3619"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Nicolo Botteghi","raw_affiliation_strings":["Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113848727","display_name":"Khaled Alaa","orcid":null},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Khaled Alaa","raw_affiliation_strings":["Intelligent Driving Functions R&D Center, IAV GmbH (Volkswagen Group), Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Driving Functions R&D Center, IAV GmbH (Volkswagen Group), Berlin, Germany","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046610258","display_name":"Mannes Poel","orcid":"https://orcid.org/0000-0002-3813-9732"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Mannes Poel","raw_affiliation_strings":["Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056056423","display_name":"Beril S\u0131rma\u00e7ek","orcid":"https://orcid.org/0000-0002-0343-5072"},"institutions":[{"id":"https://openalex.org/I94616838","display_name":"J\u00f6nk\u00f6ping University","ror":"https://ror.org/03t54am93","country_code":"SE","type":"education","lineage":["https://openalex.org/I94616838"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Beril Sirmacek","raw_affiliation_strings":["J\u00f6nk\u00f6ping University, J\u00f6nk\u00f6ping, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J\u00f6nk\u00f6ping University, J\u00f6nk\u00f6ping, Sweden","institution_ids":["https://openalex.org/I94616838"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078725649","display_name":"Christoph Br\u00fcne","orcid":"https://orcid.org/0000-0003-0145-5069"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Christoph Brune","raw_affiliation_strings":["Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012747778","display_name":"Abeje Y. Mersha","orcid":"https://orcid.org/0000-0003-0457-5293"},"institutions":[{"id":"https://openalex.org/I2801398864","display_name":"Saxion","ror":"https://ror.org/005t9n460","country_code":"NL","type":"education","lineage":["https://openalex.org/I2801398864"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Abeje Mersha","raw_affiliation_strings":["Research Group of Mechatronics, Saxion University of Applied Sciences, Enschede, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Group of Mechatronics, Saxion University of Applied Sciences, Enschede, The Netherlands","institution_ids":["https://openalex.org/I2801398864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047812798","display_name":"Stefano Stramigioli","orcid":"https://orcid.org/0000-0001-8212-7387"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Stefano Stramigioli","raw_affiliation_strings":["Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6342,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70452865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"190","last_page":"197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9984999895095825,"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":0.9984999895095825,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980000257492065,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.995199978351593,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7561423778533936},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6937268972396851},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6666629314422607},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6476733088493347},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.6405693292617798},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5874749422073364},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4674912989139557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3638495206832886},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3596775233745575},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3031492829322815},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15195947885513306},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.12307083606719971},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05522340536117554}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7561423778533936},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6937268972396851},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6666629314422607},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6476733088493347},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.6405693292617798},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5874749422073364},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4674912989139557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3638495206832886},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3596775233745575},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3031492829322815},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15195947885513306},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.12307083606719971},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05522340536117554},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iros51168.2021.9635936","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9635936","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:ris.utwente.nl:openaire/ab364560-9fd6-47dc-b195-cb424c5d8f51","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/ab364560-9fd6-47dc-b195-cb424c5d8f51","pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Botteghi, N, Alaa, K, Poel, M, Sirma\u00e7ek, B, Brune, C, Mersha, A & Stramigioli, S 2021, Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces. in IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021. IEEE International Conference on Intelligent Robots and Systems, IEEE, pp. 190-197, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021, Prague, Czech Republic, 27/09/21. https://doi.org/10.1109/IROS51168.2021.9635936","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:hbo:oai:hbokennisbank.nl:saxion_kenniscentra:3F6FF26F-4A5D-41F9-B2B25FA7C3AA47A5","is_oa":true,"landing_page_url":"https://resolver.saxion.nl/display_details/3F6FF26F-4A5D-41F9-B2B25FA7C3AA47A5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:ris.utwente.nl:openaire/ab364560-9fd6-47dc-b195-cb424c5d8f51","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/ab364560-9fd6-47dc-b195-cb424c5d8f51","pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Botteghi, N, Alaa, K, Poel, M, Sirma\u00e7ek, B, Brune, C, Mersha, A & Stramigioli, S 2021, Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces. in IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021. IEEE International Conference on Intelligent Robots and Systems, IEEE, pp. 190-197, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021, Prague, Czech Republic, 27/09/21. https://doi.org/10.1109/IROS51168.2021.9635936","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W834081922","https://openalex.org/W1164749991","https://openalex.org/W1757796397","https://openalex.org/W1977655452","https://openalex.org/W2076337359","https://openalex.org/W2089468765","https://openalex.org/W2094024286","https://openalex.org/W2100495367","https://openalex.org/W2121863487","https://openalex.org/W2124267516","https://openalex.org/W2155007355","https://openalex.org/W2163922914","https://openalex.org/W2173248099","https://openalex.org/W2257979135","https://openalex.org/W2567455162","https://openalex.org/W2619484182","https://openalex.org/W2754695199","https://openalex.org/W2766447205","https://openalex.org/W2787666871","https://openalex.org/W2889732123","https://openalex.org/W2941078345","https://openalex.org/W2948271667","https://openalex.org/W2963428623","https://openalex.org/W2963488340","https://openalex.org/W2963521487","https://openalex.org/W2963864421","https://openalex.org/W2964161785","https://openalex.org/W3008165446","https://openalex.org/W3046387304","https://openalex.org/W3125947392","https://openalex.org/W4287863878","https://openalex.org/W4288335419","https://openalex.org/W4294226150","https://openalex.org/W4298857966","https://openalex.org/W4367295663","https://openalex.org/W6623316541","https://openalex.org/W6637967152","https://openalex.org/W6682849425","https://openalex.org/W6684921986","https://openalex.org/W6758582604","https://openalex.org/W6763088550","https://openalex.org/W6779827379","https://openalex.org/W6781842715","https://openalex.org/W7034240210"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W2111669074","https://openalex.org/W2085259108","https://openalex.org/W3123087812","https://openalex.org/W2063076820"],"abstract_inverted_index":{"Reinforcement":[0,42],"learning":[1,60,78],"algorithms":[2],"have":[3],"proven":[4],"to":[5,122],"be":[6,153],"capable":[7],"of":[8,29,35,61,79,95,102,113,135,149],"solving":[9],"complicated":[10],"robotics":[11],"tasks":[12],"in":[13,26,31,92,99,117,132],"an":[14],"end-to-end":[15],"fashion":[16],"without":[17,126],"any":[18],"need":[19],"for":[20],"hand-crafted":[21],"features":[22],"or":[23],"policies.":[24],"Especially":[25],"the":[27,33,59,71,77,80,84,93,100,111,118,123,133],"context":[28,94],"robotics,":[30],"which":[32],"cost":[34],"real-world":[36,130],"data":[37,131],"is":[38],"usually":[39],"extremely":[40],"high,":[41],"Learning":[43],"solutions":[44],"achieving":[45],"high":[46],"sample":[47],"efficiency":[48],"are":[49],"needed.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,109],"propose":[55],"a":[56,62],"framework":[57,91],"combining":[58],"low-dimensional":[63],"state":[64,86,104],"representation,":[65],"from":[66,70],"high-dimensional":[67],"observations":[68],"coming":[69],"robot\u2019s":[72],"raw":[73],"sensory":[74],"readings,":[75],"with":[76],"optimal":[81],"policy,":[82],"given":[83],"learned":[85,116],"representation.":[87],"We":[88],"evaluate":[89],"our":[90,150],"mobile":[96],"robot":[97,125],"navigation":[98],"case":[101],"continuous":[103],"and":[105,137,144],"action":[106],"spaces.":[107],"Moreover,":[108],"study":[110],"problem":[112],"transferring":[114],"what":[115],"simulated":[119],"virtual":[120],"environment":[121],"real":[124],"further":[127],"retraining":[128],"using":[129],"presence":[134],"visual":[136],"depth":[138],"distractors,":[139],"such":[140],"as":[141],"lighting":[142],"changes":[143],"moving":[145],"obstacles.":[146],"A":[147],"video":[148],"experiments":[151],"can":[152],"found":[154],"at:":[155],"https://youtu.be/rUdGPKr2Wuo.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}