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Robot Attitude Estimation Based on Kalman Filter and Application to Balance Control

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Abstract:

To solve inertial sensors in the presence of random error for robot balance control, this paper proposes a simple and practical Kalman filter (KF) algorithm, which was implemented to information fusion for inclinometer and gyroscope, thus get optimal estimation for the robot attitude signal after sensors error compensation. The experimental results showed that the method based on KF to obtain the optimal estimation is effective and feasible. Through the simulation including balancing control experiment and disturb experiment, the two-wheeled robot by using LQR method can keep balance in fixed position well by the proposed method. Comparing to the method not using KF we can verify the feasibility and effectiveness of the KF attitude estimation method. The robot has a better ability of self-balancing control after using KF.

Keywords: DATA FUSION; INERTIAL SENSORS; KALMAN FILTER; TWO-WHEELED ROBOT BALANCE CONTROL

Document Type: Research Article

DOI: https://doi.org/10.1166/asl.2012.2238

Publication date: 2012-03-01

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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