WEKO3
インデックスリンク
アイテム
H∞ filtering convergence and it's application to SLAM
http://hdl.handle.net/2297/24274
http://hdl.handle.net/2297/24274afa13fdf-de2a-4d28-8ded-ea00d36317e2
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TE-PR-AHMAD-H-2875.pdf (663.6 kB)
|
|
| Item type | 会議発表論文 / Conference Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2017-10-03 | |||||
| タイトル | ||||||
| タイトル | H∞ filtering convergence and it's application to SLAM | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| 著者 |
Ahmad, Hamzah
× Ahmad, Hamzah× Namerikawa, Toru |
|||||
| 提供者所属 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 金沢大学理工研究域電子情報学系 | |||||
| 書誌情報 |
ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings 号 5333855, p. 2875-2880, 発行日 2009-01-01 |
|||||
| 出版者 | ||||||
| 出版者 | IEEE = Institute of Electrical and Electronics Engineers | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | 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. | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
