Attractive ellipsoid method controller under noised measurements for SLAM

This paper presents a novel algorithm for Simultaneous Localization and Mapping (SLAM) of mobile robots. The proposed algorithm, termed as SLAM using on Attractive Ellipsoid Method (AEM) and Luenberger filter-type application with nonlinear models, under the hypothesis that errors affecting all sensor's measurements and robot's motions are unknown-but-bounded. We suggest to select the best parameters of the suggested observer providing a minimal size of this attractive ellipsoid. It is shown that this optimization problem may be converted into the trace optimization of this attractive ellipsoid under some specific constraints of a set of LMI's (Linear Matrix Inequalities). Simulated indoor experiments are used to demonstrate the performance of the proposed algorithm.