Localizability Estimation based on Occupancy Grid Maps

Abstract

Simultaneous localization and mapping (SLAM) is a widely used technique in autonomous mobile robots. This study deals with the estimation of localizability, which indicates the reliability of localization at each location on the occupancy grid maps created by SLAM. There are several approaches to estimate localizability, this paper proposes a method using local map correlation. Our method represents the localizability using a covariance matrix of a Gaussian distribution, not just a scalar value. The simulation experiment results showed that the uncertainty of localizability increased at locations where degeneration is likely to occur, suggesting that localizability could be estimated appropriately.