Image-based position estimation of UAV using Kalman Filter

Takaaki Kojima, Toru Namerikawa

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

This paper deals with the position estimation problem by using the Kalman Filter with compensations for unexpected observations. In the position estimation problem, robot observations sometimes yield unexpected values, resulting in the deterioration of the estimation accuracy. For example, visual observation with an unmanned aerial vehicle often yields unexpected results because of blurred images. In this paper, we propose a method to assigns weights to the observations in order to remove the effects of unexpected observations. In the proposed method, unexpected observations are detected by comparing the observation values with its estimates; the weights of these observations are then determined. On the basis of simulation and experimental results, we demonstrate that a robot's position can be estimated by the proposed method.

本文言語English
ホスト出版物のタイトル2015 IEEE Conference on Control and Applications, CCA 2015 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ406-411
ページ数6
ISBN(印刷版)9781479977871
DOI
出版ステータスPublished - 2015 11月 4
イベントIEEE Conference on Control and Applications, CCA 2015 - Sydney, Australia
継続期間: 2015 9月 212015 9月 23

Other

OtherIEEE Conference on Control and Applications, CCA 2015
国/地域Australia
CitySydney
Period15/9/2115/9/23

ASJC Scopus subject areas

  • 制御およびシステム工学

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