Title :
Simultaneous pedestrian and multiple mobile robots localization using distributed extended Kalman filter
Author :
Song, Il Young ; Kim, Du Yong ; Ahn, Hyo-Sung ; Shin, Vladimir
Author_Institution :
Sch. of Inf. & Mechatron., Gwangju Inst. of Sci. & Technol., Seoul
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.
Keywords :
Kalman filters; distributed algorithms; mobile robots; multi-robot systems; nonlinear filters; path planning; distributed algorithm; distributed extended Kalman filter; multiple mobile robot localization; simultaneous pedestrian; Biomimetics; Distributed algorithms; Equations; Filtering; Mobile robots; Navigation; Orbital robotics; Robot control; Robot kinematics; Robot localization; Distributed fusion; Extended Kalman filter; Fusion formula; Multirobot localization;
Conference_Titel :
Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4244-2678-2
Electronic_ISBN :
978-1-4244-2679-9
DOI :
10.1109/ROBIO.2009.4913148