A systematic representation method of the odometry uncertainty of mobile robots

Abstract

A covariance matrix is a toot that expresses the odometry uncertainty of mobile robots. The covariance matrix is a key factor in various localization algorithms such as the Kalman filter or topological matching. However, it is not easy to acquire an accurate covariance matrix because the real states of robots are not known. Till now, few results on estimating the covariance matrix have been reported. Also, those are not validated by experiments or do not reflect the real phenomena. In this paper, we propose a novel method which approximates the covariance matrix in a physically reasonable way. Extensive experiments validate that our method yields a covariance matrix which is accurate enough for practical uses.