Simultaneous pedestrian and multiple mobile robots localization using distributed extended Kalman filter

Abstract

This paper is concerned with distributed extended Kalman filtering (DEKF) for simultaneous pedestrian and multiple mobile robots localization. Here, extended Kalman filter (EKF) is applied to the multiple robots for the pedestrian localization. The estimate from each robot is fused by distributed algorithm to improve the accuracy. Furthermore, we used multiple robots formation control to keep a triangle formation at the same time. The focus of this paper is to investigate the effect of the proposed algorithm on simultaneous localization accuracy. A Monte Carlo simulation result is presented to demonstrate the efficiency in localization accuracy of the distributed fusion of EKFs.