{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219859","sets":["1164:4061:10837:10976"]},"path":["10976"],"owner":"44499","recid":"219859","title":["What Can Data-driven Calibration Do for 6DOF Inertial Odometry?"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-08-29"},"_buckets":{"deposit":"82f78b3b-e255-49da-8fbd-da03bb8aead9"},"_deposit":{"id":"219859","pid":{"type":"depid","value":"219859","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"What Can Data-driven Calibration Do for 6DOF Inertial Odometry?","author_link":["573964","573971","573972","573965","573963","573969","573967","573970","573968","573966"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"What Can Data-driven Calibration Do for 6DOF Inertial Odometry?"},{"subitem_title":"What Can Data-driven Calibration Do for 6DOF Inertial Odometry?","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"行動認識:IMU","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-08-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology"},{"subitem_text_value":"Nara Institute of Science and Technology"},{"subitem_text_value":"Nara Institute of Science and Technology"},{"subitem_text_value":"Nara Institute of Science and Technology"},{"subitem_text_value":"Nara Institute of Science and Technology"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/219859/files/IPSJ-UBI22075008.pdf","label":"IPSJ-UBI22075008.pdf"},"date":[{"dateType":"Available","dateValue":"2024-08-29"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-UBI22075008.pdf","filesize":[{"value":"2.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"36"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"15ae0428-e09f-4f96-93d6-352a48cd7648","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Huakun, Liu"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Monica, Perusquía-Hernández"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Naoya, Isoyama"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideaki, Uchiyama"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kiyoshi, Kiyokawa"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Huakun, Liu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Monica, Perusquía-Hernández","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Naoya, Isoyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideaki, Uchiyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kiyoshi, Kiyokawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11838947","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":"2188-8698","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"For low-cost IMU, the uncalibrated bias and noise will quickly propagate 6DOF odometry errors over time. This paper proposes a data-driven accelerometer calibration method based on a dilated convolution network. Then, with a state-of-the-art gyroscope calibration method, we comprehensively analyze the impact of data-driven calibration on 6DOF inertial odometry. The experimental results show that our data-driven accelerometer calibration can reduce the bias by a factor of 5 to 10 and decreases the noise by a factor of 2 to 5. Through our exhaustive evaluations and analysis of data-driven calibration methods, the primary finding is that the data-driven calibration methods can slow down the error growth rate by 40-200 times. However, the effect of accelerometer calibration is only noticeable after calibrating the gyroscope. This fact would be experimental support for the design of future data-driven 6DOF inertial odometry.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"For low-cost IMU, the uncalibrated bias and noise will quickly propagate 6DOF odometry errors over time. This paper proposes a data-driven accelerometer calibration method based on a dilated convolution network. Then, with a state-of-the-art gyroscope calibration method, we comprehensively analyze the impact of data-driven calibration on 6DOF inertial odometry. The experimental results show that our data-driven accelerometer calibration can reduce the bias by a factor of 5 to 10 and decreases the noise by a factor of 2 to 5. Through our exhaustive evaluations and analysis of data-driven calibration methods, the primary finding is that the data-driven calibration methods can slow down the error growth rate by 40-200 times. However, the effect of accelerometer calibration is only noticeable after calibrating the gyroscope. This fact would be experimental support for the design of future data-driven 6DOF inertial odometry.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"10","bibliographic_titles":[{"bibliographic_title":"研究報告ユビキタスコンピューティングシステム（UBI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-08-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2022-UBI-75"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219859,"updated":"2025-01-19T14:45:18.472977+00:00","links":{},"created":"2025-01-19T01:19:54.962884+00:00"}