Measurement Outlier-resistant Mobile Robot Localization

This paper is concerned with the measurement outlier (MO)-resistant mobile robot localization (MRL) problem. For the purpose of mitigating the effect of the MOs, a time-varying state estimator is constructed containing a saturation function with variable saturation level. The purpose of this paper is mainly to seek an effective solution to the addressed MRL problem by devising the desired time-varying state estimator which ensures that, over a finite horizon, the estimation error dynamics satisfies the H-& INFIN; performance constraint. By constructing an appropriate Lyapunov function, the existing condition of the estimator is first obtained. Then, the desired state estimator gain is given through the solution to a set of certain matrix inequalities and the MO-resistant MRL algorithm is presented. Finally, an example is conducted to testify the usefulness of the MRL algorithm proposed.

Automated summary

This paper addresses the issue of measurement outlier (MO)-resistant mobile robot localization (MRL). A time-varying state estimator with a saturation function containing variable saturation level is proposed to mitigate the effect of MOs. The goal is to devise an effective solution for the MRL problem by ensuring that the estimation error dynamics meets the H-∞ performance constraint over a finite horizon. The paper derives the existing condition of the estimator by constructing an appropriate Lyapunov function, and provides the desired state estimator gain through solving a set of matrix inequalities, presenting the MO-resistant MRL algorithm. An example is conducted to demonstrate the usefulness of the proposed MRL algorithm.