{"created":"2023-07-27T06:25:06.452836+00:00","id":8270,"links":{},"metadata":{"_buckets":{"deposit":"9a635cdf-c657-472f-a0f6-a89654922ce6"},"_deposit":{"created_by":3,"id":"8270","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"8270"},"status":"published"},"_oai":{"id":"oai:kanazawa-u.repo.nii.ac.jp:00008270","sets":["934:935:936"]},"author_link":["11511","9725"],"item_8_biblio_info_8":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2009-01-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5333855","bibliographicPageEnd":"2880","bibliographicPageStart":"2875","bibliographic_titles":[{"bibliographic_title":"ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings"}]}]},"item_8_description_21":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"KF-SLAM(Kalman filter-SLAM) have been used as a popular solution by researchers in many SLAM application. Nevertheless, it shortcomings of assumption for Gaussian noise limited its efficiency and demand researcher to consider better filter and algorithm to achieve a promising result of estimation. In this paper, we proposed one of its family, the H ∞ filter-based SLAM to determine its competency for SLAM problem. Unlike Kalman filter, H∞ filter able to work in an unknown statistical noise behavior and thus more robust. It rely on a guess that the noise is in bounded energy and does not require a priori knowledge about the system. Therefore, we proposed the H∞ filter as other available technique to infer the location for both robot and landmarks while simultaneously building the map. From the results of simulation, H ∞ filter produces better outcome than the Kalman filter especially in the linear case estimation. As a result, H∞ filter may provides another available estimation methods with the capability to ensure and improve estimation for the robotic mapping problem especially in SLAM. © 2009 SICE.","subitem_description_type":"Abstract"}]},"item_8_description_5":{"attribute_name":"提供者所属","attribute_value_mlt":[{"subitem_description":"金沢大学理工研究域電子情報学系","subitem_description_type":"Other"}]},"item_8_publisher_17":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE = Institute of Electrical and Electronics Engineers"}]},"item_8_version_type_25":{"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":"Ahmad, Hamzah"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Namerikawa, Toru"}],"nameIdentifiers":[{},{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-10-03"}],"displaytype":"detail","filename":"TE-PR-AHMAD-H-2875.pdf","filesize":[{"value":"663.6 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"TE-PR-AHMAD-H-2875.pdf","url":"https://kanazawa-u.repo.nii.ac.jp/record/8270/files/TE-PR-AHMAD-H-2875.pdf"},"version_id":"81617afa-bf1e-4582-b25e-74be9d7cd7f4"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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":"H∞ filtering convergence and it's application to SLAM","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"H∞ filtering convergence and it's application to SLAM"}]},"item_type_id":"8","owner":"3","path":["936"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-10-03"},"publish_date":"2017-10-03","publish_status":"0","recid":"8270","relation_version_is_last":true,"title":["H∞ filtering convergence and it's application to SLAM"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-07-28T02:11:32.792289+00:00"}