{"id":"https://openalex.org/W7131828567","doi":"https://doi.org/10.1109/sii64115.2026.11404589","title":"Tactile-based Active Inference for Force-Controlled Peg-in-Hole Insertions","display_name":"Tactile-based Active Inference for Force-Controlled Peg-in-Hole Insertions","publication_year":2026,"publication_date":"2026-01-11","ids":{"openalex":"https://openalex.org/W7131828567","doi":"https://doi.org/10.1109/sii64115.2026.11404589"},"language":null,"primary_location":{"id":"doi:10.1109/sii64115.2026.11404589","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii64115.2026.11404589","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5091505184","display_name":"Tatsuya Kamijo","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuya Kamijo","raw_affiliation_strings":["The University of Tokyo,Faculty of Engineering,Department of Mechanical Engineering,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Faculty of Engineering,Department of Mechanical Engineering,Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064317353","display_name":"Ixchel G. Ram\u00edrez-Alpizar","orcid":"https://orcid.org/0000-0002-7805-7539"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ixchel G. Ramirez-Alpizar","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology (AIST),Task Intelligent Research Team, Intelligent Systems Research Institute,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology (AIST),Task Intelligent Research Team, Intelligent Systems Research Institute,Tokyo,Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040490415","display_name":"Enrique Coronado","orcid":null},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Enrique Coronado","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology (AIST),Task Intelligent Research Team, Intelligent Systems Research Institute,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology (AIST),Task Intelligent Research Team, Intelligent Systems Research Institute,Tokyo,Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"last","author":{"id":null,"display_name":"Gentiane Venture","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gentiane Venture","raw_affiliation_strings":["The University of Tokyo,Faculty of Engineering,Department of Mechanical Engineering,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Faculty of Engineering,Department of Mechanical Engineering,Japan","institution_ids":["https://openalex.org/I161296585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"161","last_page":"166"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.4797999858856201,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.4797999858856201,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10789","display_name":"Interactive and Immersive Displays","score":0.08049999922513962,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.07479999959468842,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6692000031471252},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6439999938011169},{"id":"https://openalex.org/keywords/active-vision","display_name":"Active vision","score":0.5077000260353088},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.487199991941452},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4830999970436096},{"id":"https://openalex.org/keywords/grippers","display_name":"Grippers","score":0.4787999987602234},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.46639999747276306},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.40130001306533813},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.39809998869895935}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6708999872207642},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6692000031471252},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6439999938011169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6292999982833862},{"id":"https://openalex.org/C193611912","wikidata":"https://www.wikidata.org/wiki/Q4677596","display_name":"Active vision","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.4787999987602234},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.46639999747276306},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.40130001306533813},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3734999895095825},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3718000054359436},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C2780527621","wikidata":"https://www.wikidata.org/wiki/Q7936593","display_name":"Visual control","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.3296000063419342},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.263700008392334},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C10912380","wikidata":"https://www.wikidata.org/wiki/Q527952","display_name":"Visual servoing","level":3,"score":0.25440001487731934},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sii64115.2026.11404589","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii64115.2026.11404589","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2110697446","https://openalex.org/W2110698781","https://openalex.org/W2148764920","https://openalex.org/W2167340365","https://openalex.org/W2753555157","https://openalex.org/W2775635818","https://openalex.org/W2967509406","https://openalex.org/W2976738340","https://openalex.org/W2999994890","https://openalex.org/W3017302611","https://openalex.org/W3028308378","https://openalex.org/W3081200565","https://openalex.org/W3205950068","https://openalex.org/W4313442619","https://openalex.org/W4383066145"],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0],"Learning":[1],"(RL)":[2],"has":[3],"shown":[4],"great":[5],"promise":[6],"for":[7,63],"efficiently":[8],"learning":[9],"force":[10,81],"control":[11,82],"policies":[12],"in":[13,30],"peg-in-hole":[14],"tasks.":[15],"However,":[16],"robots":[17],"often":[18],"face":[19],"difficulties":[20],"due":[21],"to":[22,85,103,161],"visual":[23],"occlusions":[24],"by":[25],"the":[26,31,36,51,55,61,87,90,93,105,109,144],"gripper":[27],"and":[28,83],"uncertainties":[29],"initial":[32],"grasping":[33],"pose":[34],"of":[35,127,146],"peg.":[37],"In":[38,111],"this":[39],"paper,":[40],"we":[41,150],"propose":[42],"a":[43,72,122,125],"robust":[44],"tactile":[45,101,138],"insertion":[46],"policy":[47,76,95],"that":[48,136],"can":[49],"align":[50,104],"tilted":[52,106],"peg":[53,107],"with":[54,108,124,153],"hole":[56,123],"using":[57],"active":[58,97],"inference,":[59],"without":[60],"need":[62],"extensive":[64],"training":[65],"on":[66,78,100],"large":[67],"datasets.":[68],"Our":[69],"approach":[70],"employs":[71],"dual-policy":[73,115],"architecture:":[74],"one":[75],"focuses":[77],"insertion,":[79],"integrating":[80],"RL":[84],"guide":[86],"object":[88],"into":[89,121],"hole,":[91],"while":[92],"other":[94],"performs":[96],"inference":[98],"based":[99],"feedback":[102,140],"hole.":[110],"real-world":[112],"experiments,":[113],"our":[114,147],"architecture":[116],"achieved":[117],"90%":[118],"success":[119],"rate":[120],"clearance":[126],"less":[128],"than":[129],"0.1":[130],"mm,":[131],"significantly":[132],"outperforming":[133],"previous":[134],"methods":[135],"lack":[137],"sensory":[139],"(5%).":[141],"To":[142],"assess":[143],"generalizability":[145],"alignment":[148],"policy,":[149],"conducted":[151],"experiments":[152],"five":[154],"different":[155],"pegs,":[156],"demonstrating":[157],"its":[158],"effective":[159],"adaptation":[160],"multiple":[162],"objects.":[163]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-28T00:00:00"}