{"updated":"2025-01-19T09:18:34.756637+00:00","links":{},"created":"2025-01-19T01:38:17.672657+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00236312","sets":["6504:11678:11689"]},"path":["11689"],"owner":"44499","recid":"236312","title":["物体検出を用いたロボットナビゲーションにおけるDeep Q-Networkの学習効率化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"47760fd0-3169-4637-a9e1-241d0829e4f2"},"_deposit":{"id":"236312","pid":{"type":"depid","value":"236312","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"物体検出を用いたロボットナビゲーションにおけるDeep Q-Networkの学習効率化","author_link":["645906","645905"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"物体検出を用いたロボットナビゲーションにおけるDeep Q-Networkの学習効率化"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東海大"},{"subitem_text_value":"東海大"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/236312/files/IPSJ-Z86-2X-02.pdf","label":"IPSJ-Z86-2X-02.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-2X-02.pdf","filesize":[{"value":"410.7 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"a108f69c-66a9-43b5-ac6c-640ffe921636","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"押鐘, 悠貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"尾関, 智子"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"従来のロボットナビゲーション方法に自己位置推定と地図構築(SLAM)がある．SLAMは精密なナビゲーションを実現する一方で，事前に正確な地図構築を必要とする．正確な地図構築には時間と労力がかかり，専門的な知識を必要とする．本研究はセンサーにRGB-Dカメラと2D-LiDARを用い，深層強化学習により事前地図構築なしにナビゲーションを行う．その際ゴールにある目標物に対して物体検出を行う．物体検出とRGB-Dカメラの深度情報を組み合わせることで，ナビゲーションを実現する．シミュレータはGazebo，ロボットはJetson Nano Mouseを用い通信制御方法としてROSを用いる．学習には，Deep Q-Networkを用い，任意のスタートからゴールまでの自律走行を学習させる．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"960","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"959","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":236312}