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Attitude determination using vector observations and the related Adaptive Optimal-REQUEST algorithm are studied. Analysis of Optimal-REQUEST's characteristic is listed. In the condition that the observe noise changes frequently, improved adaptive method is imported. The model noise is estimated real-timely and it is used in the updating of states. The simulation indicated that the algorithm could...
This paper addresses the estimation problem for linear system with linear equality state constraints. We review the existing state projection method and present a simple way to find the optimal filter gain of the constrained Kalman filter. Then, we transform the constrained system into a reduced-order model and construct a reduced-order Kalman filter for this estimation problem. Next, we discuss the...
In this paper, we address a method for improving the accuracy of the feature map from the extended Kalman filter based SLAM (EKF SLAM) by estimating the systematic parameters of the robot. Most error of the robot while traveling is divided into two categories: systematic and non systematic error. The systematic error contributes much more to odometry errors than non systematic one on most smooth indoor...
This paper addresses a novel approach to the solution of the simultaneous localization and mapping (SLAM) problem bared on a neuro evolutionary optimization (NeoSLAM) method. The proposed algorithm first casts SLAM as a global optimization problem using the cost function which represents the quality of robot pose trajectory and the feature positions in world coordinate frame. In our algorithm, the...
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