Title :
Analysis of multirobot localization uncertainty propagation
Author :
Roumeliotis, Stergios I. ; Rekleitis, Ioannis M.
Author_Institution :
Dept. of Comput. Sci. & Eng., Minnesota Univ., MN, USA
Abstract :
This paper deals with the problem of cooperative localization for the case of large groups of mobile robots. A Kalman filter estimator is implemented and tested for this purpose. The focus of this paper is to examine the effect on localization accuracy of the number N of participating robots and the accuracy of the sensors employed. More specifically, we investigate the improvement in localization accuracy per additional robot as the size of the team increases. Furthermore, we provide an analytical expression for the upper bound on the positioning uncertainty increase rate for a team of N robots as a function of N, the odometric and orientation uncertainty for each robot, and the accuracy of a robot tracker measuring relative positions between pairs of robots. The analytical results derived in this paper are validated in simulation for different test cases.
Keywords :
Kalman filters; Riccati equations; cooperative systems; covariance matrices; mobile robots; multi-robot systems; uncertainty handling; Kalman filter estimator; Ricatti equation; cooperative localization; covariance matrix; homogeneous robot team; mobile robots; multirobot localization; uncertainty propagation; Analytical models; Computer science; Mechanical engineering; Mobile robots; Position measurement; Riccati equations; Robot sensing systems; Testing; Uncertainty; Upper bound;
Conference_Titel :
Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on
Print_ISBN :
0-7803-7860-1
DOI :
10.1109/IROS.2003.1248899