{"_buckets": {"deposit": "0fa4b73b-8f7b-4949-9d10-f8ab522fc849"}, "_deposit": {"created_by": 3, "id": "1516", "owners": [3], "pid": {"revision_id": 0, "type": "depid", "value": "1516"}, "status": "published"}, "_oai": {"id": "oai:kyutech.repo.nii.ac.jp:00001516", "sets": ["20"]}, "author_link": ["6091", "3456", "6093"], "item_23_alternative_title_18": {"attribute_name": "その他のタイトル", "attribute_value_mlt": [{"subitem_alternative_title": "System Identification of an AUV using mnSOM"}]}, "item_23_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2006-05-26", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "1P1-E23(4)", "bibliographicPageStart": "1P1-E23(1)", "bibliographic_titles": [{"bibliographic_title": "ロボティクス・メカトロニクス講演会2006講演論文集"}]}]}, "item_23_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "Autonomous Underwater Vehicles(AUVs) are attractive tools to survey earth science and oceanography, however,there exists a lot of problems to be solved such as motion control, acquisition of sensor data, decision-making, navigation without collision, self-localization and so on. In order to realize useful and practical robots, underwater vehicles should take their action by judging the changing condition from their own sensors and actuators, and are desirable to make their behavior, because of features caused by the working envirornment. We have been investigated the application of brain-inspired technologies such as Neural Networks(NNs), Self-Organizing Map(SOM), etc, into AUVs_A new self-organizing decision making system for AUVs using Modular Network Self-Organizing Map(mnSOM) proposed by Tokunaga et al. is discussed in this paper.The proposed decision making system is developed using recurrent NN type mnSOM.The efficiency of the system is investigated through the simulations.", "subitem_description_type": "Abstract"}]}, "item_23_description_5": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "ロボティクス・メカトロニクス講演会 2006，2006年5月26日，早稲田大学，日本", "subitem_description_type": "Other"}]}, "item_23_description_60": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"subitem_description": "Conference Paper", "subitem_description_type": "Other"}]}, "item_23_full_name_3": {"attribute_name": "著者別名", "attribute_value_mlt": [{"nameIdentifiers": [{"nameIdentifier": "6093", "nameIdentifierScheme": "WEKO"}], "names": [{"name": "Nishida, Shuhei"}]}, {"nameIdentifiers": [{"nameIdentifier": "3456", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "10291527", "nameIdentifierScheme": "e-Rad", "nameIdentifierURI": "https://nrid.nii.ac.jp/ja/nrid/1000010291527/"}, {"nameIdentifier": "7403966003", "nameIdentifierScheme": "Scopus著者ID", "nameIdentifierURI": "https://www.scopus.com/authid/detail.uri?authorId=7403966003"}, {"nameIdentifier": "353", "nameIdentifierScheme": "九工大研究者情報", "nameIdentifierURI": "https://hyokadb02.jimu.kyutech.ac.jp/html/353_ja.html"}], "names": [{"name": "Ishii, Kazuo"}]}]}, "item_23_publisher_7": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "社団法人日本機械学会"}]}, "item_23_text_37": {"attribute_name": "著者所属", "attribute_value_mlt": [{"subitem_text_value": "九州工業大学"}, {"subitem_text_value": "Kyushu Institute of Technology"}]}, "item_23_text_63": {"attribute_name": "業績ID", "attribute_value_mlt": [{"subitem_text_value": "99F6497EA6278903492575920024E948"}]}, "item_23_version_type_58": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_970fb48d4fbd8a85", "subitem_version_type": "VoR"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "西田, 周平"}], "nameIdentifiers": [{"nameIdentifier": "6091", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "石井, 和男"}], "nameIdentifiers": [{"nameIdentifier": "3456", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "10291527", "nameIdentifierScheme": "e-Rad", "nameIdentifierURI": "https://nrid.nii.ac.jp/ja/nrid/1000010291527/"}, {"nameIdentifier": "7403966003", "nameIdentifierScheme": "Scopus著者ID", "nameIdentifierURI": "https://www.scopus.com/authid/detail.uri?authorId=7403966003"}, {"nameIdentifier": "353", "nameIdentifierScheme": "九工大研究者情報", "nameIdentifierURI": "https://hyokadb02.jimu.kyutech.ac.jp/html/353_ja.html"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2009-04-08"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "file2.pdf", "filesize": [{"value": "3.5 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 3500000.0, "url": {"label": "file2.pdf", "url": "https://kyutech.repo.nii.ac.jp/record/1516/files/file2.pdf"}, "version_id": "232a8e0a-cf96-47ad-b586-b1ed5a4abe9a"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "AUV", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Recurrent Neural Network", "subitem_subject_scheme": "Other"}, {"subitem_subject": "mnSOM", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "jpn"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "conference paper", "resourceuri": "http://purl.org/coar/resource_type/c_5794"}]}, "item_title": "モジュラーネットワーク型自己組織化マップを用いた水中ロボットのシステム同定", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "モジュラーネットワーク型自己組織化マップを用いた水中ロボットのシステム同定"}]}, "item_type_id": "23", "owner": "3", "path": ["20"], "permalink_uri": "http://hdl.handle.net/10228/2342", "pubdate": {"attribute_name": "公開日", "attribute_value": "2009-04-08"}, "publish_date": "2009-04-08", "publish_status": "0", "recid": "1516", "relation": {}, "relation_version_is_last": true, "title": ["モジュラーネットワーク型自己組織化マップを用いた水中ロボットのシステム同定"], "weko_shared_id": -1}