Filters for mobile robots: EKF, UKF and sensor switching - experimental results

Abstract

In this work we compare the performance of two well known filters for nonlinear models, the Extended Kalman Filter and the Unscented Kalman Filter, in estimating the position and orientation of a mobile robot. The two filters are driven by measurements taken by ultrasonic sensors that are located onboard the robot, and a switching sensors activation policy is devised, which allows power saving and accurate tracking. The experimental results show a substantial equivalence of the two filters, although in principle the approximating properties of the UKF are much better.