Fuzzy decentralized EIF-based pose tracking for autonomous omnidirectional mobile robot

Abstract

This paper presents a fuzzy decentralized extended information filter (FDEIF) method for dynamic pose tracking of an autonomous omnidirectional mobile robot (AOMR) driven by omnidirectional Mecanum wheels in indoor environments by fusing measurements from one KINECT sensor, one laser scanner and four encoders mounted on the omnidirectional Mecanum wheels. A FDEIF method is proposed to achieve multisensory fusing for nonlinear measurement models corrupted with time-vary noise characteristics. Assume that the initial global pose is roughly determined by the user, we proposed an FDEIF dynamic pose tracking approach to fuse the measurements from the three types of sensors, in order to accurately keep track of the dynamic postures of the robot moving at slow speeds. Numerical simulations are performed DEIF to exemplify the superior estimation performance and robustness of the proposed method in comparison with one existing DEIF method.