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Localization is a crucial part in robot navigation. The significance of this issue is to the extent that further achievements in terms of robot control is highly dependent on that. There are various methods addressing this subject, among which the extended Kalman filter is proved to be one of the most successful ones. In classic extended Kalman filter, covariance matrixes of process noise Q and measurement...
In this paper, after reviewing the traditional Kalman filter formulation, a development of a fuzzy logic-based adaptive Kalman filter is outlined. The adaptation is in the sense of adaptively tuning, on-line, the measurement noise covariance matrix R or the process noise covariance matrix Q. This improves the Kalman filter performance and prevents filter divergence when R or Q are uncertain. Based...
This work discusses the implementation of inertial navigation system aided by Doppler Velocity Log (DVL) for the Autonomous Underwater Vehicles (AUV) applications. Due to disturbance from waves, the complicated underwater environment, to achieve Strapdown Inertial Navigation System (SINS) alignment accuracy within a short period of time is still a challenging problem. The difficulty for underwater...
Electrified drive trains for tractors are supposed to realize great potential of raising performance in heavy operations via optimal traction control. The paper proposes to apply an adaptive unscented Kaiman filter (UKF) with a fuzzy supervisor for identification of electrical drive train tractor dynamics. The key advantage of electrical drive trains lies in feedback of drive torque which plays crucial...
This paper presents a sensor fusion method based on the combination of adaptive unscented Kalman filter (UKF) and Fuzzy Logic Adaptive System (FLAS) for the ultra-tightly coupled GPS/INS integrated navigation. The UKF employs a set of sigma points by deterministic sampling, such that the linearization process is not necessary, and therefore the error caused by linearization as in the traditional extended...
The present paper proposes a new adaptive Kalman filter-based multisensor fusion to satisfy the real time performance requirements. The adaptive scheme of Kalman filter based on fuzzy logic is developed to prevent the filter from divergence and to avoid the need of accurate knowledge of statistical values of noise for both process and measurement noises. To reach this objective, first each measurement...
In the paper a newly developed fuzzy adaptive Kalman filter (FAKF) algorithm is presented which is applied in miniature attitude and heading reference system (AHRS) based on MIMU/magnetometers. The method is to deal with time variable statistic of measurement noise in different working conditions. By monitoring the innovation of sensors data in realtime, the Kalman filter tunes the measurement noise...
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