Pose Estimation of Mobile Robots with Quantized Measurements using EFIR Filtering: Experimental comparison with the EKF
Konferenz: ISR 2018 - 50th International Symposium on Robotics
20.06.2018 - 21.06.2016 in München, Germany
Tagungsband: ISR 2018
Seiten: 7Sprache: EnglischTyp: PDFPersönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt
Hess, Daniel; Roehrig, Christof (University of Applied Sciences and Arts Dortmund, Germany)
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.