ROBOMECH Journal (Sep 2023)

Localizability estimation using correlation on occupancy grid maps

  • Maiku Kondo,
  • Masahiko Hoshi,
  • Yoshitaka Hara,
  • Sousuke Nakamura

DOI
https://doi.org/10.1186/s40648-023-00256-w
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 17

Abstract

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Abstract In the field of autonomous mobile robotics, reliable localization is important. However, there are real environments where localization fails. In this paper, we propose a method to estimate localizability based on occupancy grid maps. The localizability indicates the reliability of localization. There are several approaches to estimate localizability, we propose a method to estimate localizability as a covariance matrix of the Gaussian distribution using local map correlation. Our method can estimate the magnitude of the localization error and the characteristics of the error. To confirm the effectiveness of the proposed method, we constructed simulation environments that include representative shapes of indoor environments. We conducted an experiment to investigate the characteristics of the distribution of local map correlation. Furthermore, we also conducted an experiment of our method to estimate localizability on occupancy grid maps. The simulation experiment results showed that the proposed method could estimate the magnitude of the localization error and the characteristics of the error on occupancy grid maps. The proposed method was confirmed to be effective in estimating localizability.

Keywords