Bearings-only localization using nonlinear second-order extended H∞ filter

Jwu-Sheng Hu*

*Corresponding author for this work

研究成果: Conference contribution同行評審

摘要

Simultaneous localization and mapping (SLAM) is an important issue in intelligent robotic research. The existing works perform robot localization using several nonlinear Bayesian filter such as extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter, etc. To cope with different types of disturbances other than Gaussian noise, this work proposes a nonlinear filter mechanism based on the H∞ control theory. First, a nonlinear system is introduced to be expanded by using Taylor's theorem. The 3rd and higher order term are ignored. The second order extended (SOE) Kalman filter is applied to show it performance comparing with the second order extended (SOE) H∞ filter. When the noise component is not perfect Gaussian distribution, which would usually happen in practical situation, the SOE H∞ filter outperform SOE Kalman filter. Also, the SOE H∞ filter requires less computation than particle filter which is more adequate to. A simulation result is shown and an experiment is design to test its real-time function.

原文English
主出版物標題6th IFAC Symposium on Mechatronic Systems, MECH 2013
發行者IFAC Secretariat
頁面61-66
頁數6
版本5
ISBN(列印)9783902823311
DOIs
出版狀態Published - 1 一月 2013
事件6th IFAC Symposium on Mechatronic Systems, MECH 2013 - Hangzhou, China
持續時間: 10 四月 201312 四月 2013

出版系列

名字IFAC Proceedings Volumes (IFAC-PapersOnline)
號碼5
46
ISSN(列印)1474-6670

Conference

Conference6th IFAC Symposium on Mechatronic Systems, MECH 2013
國家China
城市Hangzhou
期間10/04/1312/04/13

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