Stewart Platform Manipulator: State Estimation Using Inertia Sensors and Unscented Kalman Filter

Shady A. Maged, A. A. Abouelsoud, Ahmed M R Fath El Bab, Toru Namerikawa

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

This manuscript presents the estimation of both position and velocity of Stewart manipulator using leg length measurements and MEMS inertial sensors. The estimation by using Unscented Kalman Filter (UKF) is based on the combination of different sensors. UKF is used as a nonlinear state estimator to the Stewart platform which is modeled as a stochastic differential equation due to measurement noise. The experimental results of the UKF are verified on the Stewart platform DELTALAB EX800 using LABVIEW real time software. The desired trajectories are compared with the estimated states (position and orientation) obtained using UKF. Moreover, the estimated leg lengths are compared with the real measured output from the potentiometer sensors of the six legs of the parallel manipulator. The experimental results show that the estimation error is bounded with small bound depending on the covariance matrices. This proves the effectiveness of the proposed Unscented Kalman Filter (UKF) as a nonlinear estimator with integration between inertial sensors and leg potentiometers.

本文言語English
ホスト出版物のタイトルProceedings - 2016 3rd International Conference on Information Science and Control Engineering, ICISCE 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1136-1140
ページ数5
ISBN(電子版)9781509025350
DOI
出版ステータスPublished - 2016 10 31
イベント3rd International Conference on Information Science and Control Engineering, ICISCE 2016 - Beijing, China
継続期間: 2016 7 82016 7 10

Other

Other3rd International Conference on Information Science and Control Engineering, ICISCE 2016
CountryChina
CityBeijing
Period16/7/816/7/10

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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