Sonar-based robot navigation using nonlinear-robust Kalman filter

Abstract

In this paper, we address the sonar-based navigation of mobile robots by using Kalman filtering. The extended Kalman filtering (EKF) technique is considered. For this problem, we present results on the robustness of the nonlinear observation scheme. The original feature is that the region-of-convergence question is posed in its complete nonlinear framework, that is, considering the dynamics not only of the estimation error ζ(t), but also of the covariance matrix P(t). In this way, and compared to previous results in the literature, the approach followed makes more rigorous the treatment and facilitates the convergence analysis. The proposed ideas were tested successfully on simulation experiments of a mobile platform.