{"created":"2025-02-21T03:39:14.475828+00:00","id":2007030,"links":{},"metadata":{"_buckets":{"deposit":"ceade3aa-3d0e-481b-8412-3abdfad36f31"},"_deposit":{"created_by":41,"id":"2007030","owners":[41],"pid":{"revision_id":0,"type":"depid","value":"2007030"},"status":"published"},"_oai":{"id":"oai:hiroshima.repo.nii.ac.jp:02007030","sets":["1730444907710"]},"author_link":[],"item_1617186331708":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_title":"Online Learning of Virtual Impedance Parameters in Non-Contact Impedance Control Using Neural Networks","subitem_title_language":"en"}]},"item_1617186419668":{"attribute_name":"Creator","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tsuji, Toshio","creatorNameLang":"en"}],"familyNames":[{"familyName":"Tsuji","familyNameLang":"en"}],"givenNames":[{"givenName":"Toshio","givenNameLang":"en"}]},{"creatorNames":[{"creatorName":"Terauchi, Mutsuhiro","creatorNameLang":"en"}],"familyNames":[{"familyName":"Terauchi","familyNameLang":"en"}],"givenNames":[{"givenName":"Mutsuhiro","givenNameLang":"en"}]},{"creatorNames":[{"creatorName":"Tanaka, Yoshiyuki","creatorNameLang":"en"}],"familyNames":[{"familyName":"Tanaka","familyNameLang":"en"}],"givenNames":[{"givenName":"Yoshiyuki","givenNameLang":"en"}]}]},"item_1617186476635":{"attribute_name":"Access Rights","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_1617186499011":{"attribute_name":"Rights","attribute_value_mlt":[{"subitem_rights":"Copyright (c) 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE."}]},"item_1617186609386":{"attribute_name":"Subject","attribute_value_mlt":[{"subitem_subject":"Impact control","subitem_subject_scheme":"Other"},{"subitem_subject":"impedance control","subitem_subject_scheme":"Other"},{"subitem_subject":"noncontact impedance","subitem_subject_scheme":"Other"},{"subitem_subject":"neural networks (NN)","subitem_subject_scheme":"Other"},{"subitem_subject":"robot manipulator","subitem_subject_scheme":"Other"},{"subitem_subject":"530","subitem_subject_scheme":"NDC"}]},"item_1617186626617":{"attribute_name":"Description","attribute_value_mlt":[{"subitem_description":"Impedance control is one of the most effective methods forcontrolling the interaction between a manipulator and a task environment.In conventional impedance control methods, however, the manipulatorcannot be controlled until the end-effector contacts task environments. Anoncontact impedance control method has been proposed to resolve such aproblem. This method on only can regulate the end-point impedance, butalso the virtual impedance that works between the manipulator and theenvironment by using visual information. This paper proposes a learningmethod using neural networks to regulate the virtual impedance parametersaccording to a given task. The validity of the proposed method wasverified through computer simulations and experiments with a multijointrobotic manipulator.","subitem_description_language":"en"}]},"item_1617186643794":{"attribute_name":"Publisher","attribute_value_mlt":[{"subitem_publisher":"IEEE"}]},"item_1617186702042":{"attribute_name":"Language","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_1617186920753":{"attribute_name":"Source Identifier","attribute_value_mlt":[{"subitem_source_identifier":"1083-4419","subitem_source_identifier_type":"ISSN"}]},"item_1617187024783":{"attribute_name":"Page Start","attribute_value_mlt":[{"subitem_start_page":"2112"}]},"item_1617187056579":{"attribute_name":"Bibliographic Information","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2004","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5","bibliographicPageEnd":"2118","bibliographicPageStart":"2112","bibliographicVolumeNumber":"34","bibliographic_titles":[{"bibliographic_title":"IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics"},{"bibliographic_title":"IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics"}]}]},"item_1617258105262":{"attribute_name":"Resource Type","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_1617265215918":{"attribute_name":"Version Type","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_1617353299429":{"attribute_name":"Relation","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"http://dx.doi.org/10.1109/TSMCB.2004.829133","subitem_relation_type_select":"DOI"}}]},"item_1617605131499":{"attribute_name":"File","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-03-18"}],"displaytype":"simple","filename":"IEEE_TSMC_B_C_2112-2118-2004.pdf","filesize":[{"value":"504.1 KB"}],"mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://hiroshima.repo.nii.ac.jp/record/2007030/files/IEEE_TSMC_B_C_2112-2118-2004.pdf"},"version_id":"105906b8-c10e-4527-927b-88e423c4f0d1"}]},"item_1732771732025":{"attribute_name":"旧ID","attribute_value":"14213"},"item_title":"Online Learning of Virtual Impedance Parameters in Non-Contact Impedance Control Using Neural Networks","item_type_id":"40003","owner":"41","path":["1730444907710"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-03-18"},"publish_date":"2023-03-18","publish_status":"0","recid":"2007030","relation_version_is_last":true,"title":["Online Learning of Virtual Impedance Parameters in Non-Contact Impedance Control Using Neural Networks"],"weko_creator_id":"41","weko_shared_id":-1},"updated":"2025-02-21T09:00:25.021165+00:00"}