{"created":"2025-01-19T01:25:02.648434+00:00","updated":"2025-01-19T12:46:39.179257+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00225536","sets":["1164:2822:11181:11182"]},"path":["11182"],"owner":"44499","recid":"225536","title":["強化学習を用いた3D LiDAR SLAM向け入力点群削減手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-03-16"},"_buckets":{"deposit":"da2296ce-e2e4-42c0-8f58-77a3435e64c4"},"_deposit":{"id":"225536","pid":{"type":"depid","value":"225536","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"強化学習を用いた3D LiDAR SLAM向け入力点群削減手法","author_link":["596985","596986","596988","596984","596987","596983"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"強化学習を用いた3D LiDAR SLAM向け入力点群削減手法"},{"subitem_title":"A Point-Cloud Size Reduction Technique using Reinforcement Learning for 3D LiDAR SLAM","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"深層学習","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2023-03-16","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学大学院理工学研究科"},{"subitem_text_value":"慶應義塾大学大学院理工学研究科"},{"subitem_text_value":"慶應義塾大学大学院理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Science and Technology, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Technology, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Technology, Keio University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/225536/files/IPSJ-EMB23062029.pdf","label":"IPSJ-EMB23062029.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-EMB23062029.pdf","filesize":[{"value":"1.2 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"42"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"161f8b2b-0356-4f93-baa5-525b358d2d3a","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小島, 瑠斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"杉浦, 圭祐"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松谷, 宏紀"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ryuto, Kojima","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Keisuke, Sugiura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroki, Matsutani","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12149313","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-868X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"自動運転等に応用され,自己位置推定・環境地図作成を同時に行う Lidar SLAM において点群は,アルゴリズムの根幹を成す重要なデータである.しかし点群はデータ量が非常に大きいため,ノードが相互通信する場合,全転送時のデータ量は膨大となる.本研究においては,代表的な 3 次元 Lidar SLAM アルゴリズムである LOAM を対象とし,SLAMアルゴリズムに最適化された点群の削減手法を検討する.その過程で,強化学習を用いた削減法の検討と実験を行った.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告組込みシステム(EMB)"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-03-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"29","bibliographicVolumeNumber":"2023-EMB-62"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":225536,"links":{}}