Pose Estimation of Mobile Robots with Quantized Measurements using EFIR Filtering: Experimental comparison with the EKF

The unbiased finite impulse response (UFIR) filter is a universal estimator for linear systems. The extended UFIR (EFIR) is the counterpart of the UFIR for nonlinear systems and operates similarly to the well known extended Kalman filter (EKF). Pose estimation of mobile robots with quantized position measurements is an application, where the EKF leads to suboptimal accuracy. In this paper a pose estimator for quantized measurements based on the EFIR algorithm is developed. Experimental results conducted with a mobile robot on an array of floor installed RFID tags show that the proposed algorithm outperforms the quantized EKF in many cases.